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| how to build a question answering system: Open-Domain Question Answering John Prager, 2007 Open-Domain Question Answering is an introduction to the field of Question Answering (QA). It covers the basic principles of QA along with a selection of systems that have exhibited interesting and significant techniques, so it serves more as a tutorial than as an exhaustive survey of the field. Starting with a brief history of the field, it goes on to describe the architecture of a QA system before analysing in detail some of the specific approaches that have been successfully deployed by academia and industry designing and building such systems. Open-Domain Question Answering is both a guide for beginners who are embarking on research in this area, and a useful reference for established researchers and practitioners in this field. |
| how to build a question answering system: Advances in Open Domain Question Answering Tomek Strzalkowski, Sanda Harabagiu, 2006-10-07 Automated question answering - the ability of a machine to answer questions, simple or complex, posed in ordinary human language - is one of today’s most exciting technological developments. It has all the markings of a disruptive technology, one that is poised to displace the existing search methods and establish new standards for user-centered access to information. This book gives a comprehensive and detailed look at the current approaches to automated question answering. The level of presentation is suitable for newcomers to the field as well as for professionals wishing to study this area and/or to build practical QA systems. The book can serve as a how-to handbook for IT practitioners and system developers. It can also be used to teach advanced graduate courses in Computer Science, Information Science and related disciplines. The readers will acquire in-depth practical knowledge of this critical new technology. |
| how to build a question answering system: Taming Text Grant S. Ingersoll, Thomas S. Morton, Drew Farris, 2013-01-24 Summary Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built. About this Book There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook. Taming Text is a practical, example-driven guide to working withtext in real applications. This book introduces you to useful techniques like full-text search, proper name recognition,clustering, tagging, information extraction, and summarization.You'll explore real use cases as you systematically absorb thefoundations upon which they are built.Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language. Written for Java developers, the book requires no prior knowledge of GWT. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Winner of 2013 Jolt Awards: The Best Books—one of five notable books every serious programmer should read. What's Inside When to use text-taming techniques Important open-source libraries like Solr and Mahout How to build text-processing applications About the Authors Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout,Lucene, and Solr. Takes the mystery out of verycomplex processes.—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University Table of Contents Getting started taming text Foundations of taming text Searching Fuzzy string matching Identifying people, places, and things Clustering text Classification, categorization, and tagging Building an example question answering system Untamed text: exploring the next frontier |
| how to build a question answering system: Hands-on Question Answering Systems with BERT Navin Sabharwal, Amit Agrawal, 2021-02-06 Get hands-on knowledge of how BERT (Bidirectional Encoder Representations from Transformers) can be used to develop question answering (QA) systems by using natural language processing (NLP) and deep learning. The book begins with an overview of the technology landscape behind BERT. It takes you through the basics of NLP, including natural language understanding with tokenization, stemming, and lemmatization, and bag of words. Next, you’ll look at neural networks for NLP starting with its variants such as recurrent neural networks, encoders and decoders, bi-directional encoders and decoders, and transformer models. Along the way, you’ll cover word embedding and their types along with the basics of BERT. After this solid foundation, you’ll be ready to take a deep dive into BERT algorithms such as masked language models and next sentence prediction. You’ll see different BERT variations followed by a hands-on example of a question answering system. Hands-on Question Answering Systems with BERT is a good starting point for developers and data scientists who want to develop and design NLP systems using BERT. It provides step-by-step guidance for using BERT. What You Will Learn Examine the fundamentals of word embeddings Apply neural networks and BERT for various NLP tasks Develop a question-answering system from scratch Train question-answering systems for your own data Who This Book Is For AI and machine learning developers and natural language processing developers. |
| how to build a question answering system: Question Answering over Text and Knowledge Base Saeedeh Momtazi, Zahra Abbasiantaeb, 2022-11-04 This book provides a coherent and complete overview of various Question Answering (QA) systems. It covers three main categories based on the source of the data that can be unstructured text (TextQA), structured knowledge graphs (KBQA), and the combination of both. Developing a QA system usually requires using a combination of various important techniques, including natural language processing, information retrieval and extraction, knowledge graph processing, and machine learning. After a general introduction and an overview of the book in Chapter 1, the history of QA systems and the architecture of different QA approaches are explained in Chapter 2. It starts with early close domain QA systems and reviews different generations of QA up to state-of-the-art hybrid models. Next, Chapter 3 is devoted to explaining the datasets and the metrics used for evaluating TextQA and KBQA. Chapter 4 introduces the neural and deep learning models used in QA systems. This chapter includes the required knowledge of deep learning and neural text representation models for comprehending the QA models over text and QA models over knowledge base explained in Chapters 5 and 6, respectively. In some of the KBQA models the textual data is also used as another source besides the knowledge base; these hybrid models are studied in Chapter 7. In Chapter 8, a detailed explanation of some well-known real applications of the QA systems is provided. Eventually, open issues and future work on QA are discussed in Chapter 9. This book delivers a comprehensive overview on QA over text, QA over knowledge base, and hybrid QA systems which can be used by researchers starting in this field. It will help its readers to follow the state-of-the-art research in the area by providing essential and basic knowledge. |
| how to build a question answering system: Bot Making Guide Alisa Turing, AI, 2025-02-17 Bot Making Guide offers a practical introduction to building chatbots and automation tools, essential technologies for modern businesses and individuals. It emphasizes hands-on learning, guiding readers through the process of creating intelligent bots using popular platforms like Dialogflow and Rasa. The book uniquely focuses on empowering individuals with programming knowledge to innovate and solve problems creatively, regardless of extensive resources. The guide begins with chatbot architecture and automation frameworks, progressing to simple chatbot construction utilizing natural language processing (NLP) and machine learning (ML). It then explores creating custom automation tools via APIs, with examples like automating social media or data aggregation. Did you know that chatbots can significantly enhance customer service by providing instant support and automating routine tasks? Or that automation tools extend beyond customer interaction to encompass data analysis and content generation? The later chapters discuss advanced techniques, ethical considerations, and real-world deployment strategies, offering insights into scaling and maintaining these systems. This approach ensures readers gain the skills to actively participate in the evolving digital landscape of AI development and automation. |
| how to build a question answering system: Taming Text Grant Ingersoll, Thomas S. Morton, Drew Farris, 2012-12-20 Summary Taming Text, winner of the 2013 Jolt Awards for Productivity, is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built. About this Book There is so much text in our lives, we are practically drowningin it. Fortunately, there are innovative tools and techniquesfor managing unstructured information that can throw thesmart developer a much-needed lifeline. You'll find them in thisbook. Taming Text is a practical, example-driven guide to working withtext in real applications. This book introduces you to useful techniques like full-text search, proper name recognition,clustering, tagging, information extraction, and summarization.You'll explore real use cases as you systematically absorb thefoundations upon which they are built.Written in a clear and concise style, this book avoids jargon, explainingthe subject in terms you can understand without a backgroundin statistics or natural language processing. Examples arein Java, but the concepts can be applied in any language. Written for Java developers, the book requires no prior knowledge of GWT. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. Winner of 2013 Jolt Awards: The Best Books—one of five notable books every serious programmer should read. What's Inside When to use text-taming techniques Important open-source libraries like Solr and Mahout How to build text-processing applications About the Authors Grant Ingersoll is an engineer, speaker, and trainer, a Lucenecommitter, and a cofounder of the Mahout machine-learning project. Thomas Morton is the primary developer of OpenNLP and Maximum Entropy. Drew Farris is a technology consultant, software developer, and contributor to Mahout,Lucene, and Solr. Takes the mystery out of verycomplex processes.—From the Foreword by Liz Liddy, Dean, iSchool, Syracuse University Table of Contents Getting started taming text Foundations of taming text Searching Fuzzy string matching Identifying people, places, and things Clustering text Classification, categorization, and tagging Building an example question answering system Untamed text: exploring the next frontier |
| how to build a question answering system: Foundations and Trends in Smart Learning Maiga Chang, Elvira Popescu, Kinshuk, Nian-Shing Chen, Mohamed Jemni, Ronghuai Huang, J. Michael Spector, Demetrios G. Sampson, 2019-03-14 This book focuses on the interplay between pedagogy and technology, and their fusion for the advancement of smart learning environments. It discusses various components of this interplay, including learning and assessment paradigms, social factors and policies, emerging technologies, innovative application of mature technologies, transformation of curriculum and teaching behavior, transformation of administration, best infusion practices, and piloting of new ideas. The book provides an archival forum for researchers, academics, practitioners and industry professionals interested and/or engaged in reforming teaching and learning methods by promoting smart learning environments. It also facilitates discussions and constructive dialogue among various stakeholders on the limitations of existing learning environments, the need for reform, innovative uses of emerging pedagogical approaches and technologies, and sharing and promoting best practices, leading to the evolution, design and implementation of smart learning environments. |
| how to build a question answering system: Digital Multimedia Communications Guangtao Zhai, Jun Zhou, Long Ye, Hua Yang, Ping An, 2025-04-08 This volume contains 28 selected papers presented at IFTC 2024: 21st International Forum of Digital Multimedia Communication, held in Lingshui, Hainan, China, on November 28-29, 2024. The 55 full papers included in this 2-volume set were carefully reviewed and selected from 146 submissions. They were organized in topical sections as follows: CCIS 2441: Affective Computing, Graphics & Image Processing for Virtual Reality, Large Language Models, Multimedia Communication, Application of Deep Learning and Video Analysis. CCIS 2442: Human and Interactive Media, Image Processing, Quality Assessment and Source Coding. |
| how to build a question answering system: Intelligent and Cloud Computing Debahuti Mishra, Rajkumar Buyya, Prasant Mohapatra, Srikanta Patnaik, 2020-10-30 This book features a collection of high-quality research papers presented at the International Conference on Intelligent and Cloud Computing (ICICC 2019), held at Siksha 'O' Anusandhan (Deemed to be University), Bhubaneswar, India, on December 20, 2019. Including contributions on system and network design that can support existing and future applications and services, it covers topics such as cloud computing system and network design, optimization for cloud computing, networking, and applications, green cloud system design, cloud storage design and networking, storage security, cloud system models, big data storage, intra-cloud computing, mobile cloud system design, real-time resource reporting and monitoring for cloud management, machine learning, data mining for cloud computing, data-driven methodology and architecture, and networking for machine learning systems. |
| how to build a question answering system: Proceedings of the World Conference on Intelligent and 3-D Technologies (WCI3DT 2022) Roumen Kountchev, Kazumi Nakamatsu, Wenfeng Wang, Roumiana Kountcheva, 2023-01-01 This book features a collection of high-quality, peer-reviewed research papers presented at first ‘World Conference on Intelligent and 3-D Technologies’ (WCI3DT 2022), held in China during May 24–26, 2022. The book provides an opportunity for the researchers and academia as well as practitioners from industry to publish their ideas and recent research development work on all aspects of 3D imaging technologies and artificial intelligence, their applications, and other related areas. The book presents ideas and the works of scientists, engineers, educators, and students from all over the world from institutions and industries. |
| how to build a question answering system: New Trends in Intelligent Software Methodologies, Tools and Techniques H. Fujita, A. Selamat, S. Omatu, 2017-09-07 Software is an essential enabler for science and the new economy. It creates new markets and directions for a more reliable, flexible and robust society and empowers the exploration of our world in ever more depth, but it often falls short of our expectations. Current software methodologies, tools, and techniques are still neither robust nor reliable enough for the constantly evolving market, and many promising approaches have so far failed to deliver the solutions required. This book presents the keynote ‘Engineering Cyber-Physical Systems’ and 64 peer-reviewed papers from the 16th International Conference on New Trends in Intelligent Software Methodology Tools, and Techniques, (SoMeT_17), held in Kitakyushu, Japan, in September 2017, which brought together researchers and practitioners to share original research results and practical development experience in software science and related new technologies. The aim of the SoMeT conferences is to capture the essence of the new state-of-the-art in software science and its supporting technology and to identify the challenges such technology will have to master. The book explores new trends and theories which illuminate the direction of developments in this field, and will be of interest to anyone whose work involves software science and its integration into tomorrow’s global information society. |
| how to build a question answering system: Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) Ghaffar Ali, Mehmet Cüneyt Birkök, Intakhab Alam Khan, 2023-09-16 This is an open access book. The aim of 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) is to bring together innovative academics and industrial experts in the field of Education, Management and Social Sciences to a common forum. The primary goal of the conference is to promote research and developmental activities in Education, Management and Social Sciences and another goal is to promote scientific information interchange between researchers, developers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Education, Management and Social Sciences and related areas. |
| how to build a question answering system: On the Move to Meaningful Internet Systems: OTM 2019 Conferences Hervé Panetto, Christophe Debruyne, Martin Hepp, Dave Lewis, Claudio Agostino Ardagna, Robert Meersman, 2019-10-10 This volume LNCS 11877 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C&TC, held as part of OTM 2019 in October 2019 in Rhodes, Greece. The 38 full papers presented together with 8 short papers were carefully reviewed and selected from 156 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, informationsystems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing. |
| how to build a question answering system: Knowledge and Systems Engineering Viet-Ha Nguyen, Anh-Cuong Le, Van-Nam Huynh, 2014-09-29 This volume contains papers presented at the Sixth International Conference on Knowledge and Systems Engineering (KSE 2014), which was held in Hanoi, Vietnam, during 9–11 October, 2014. The conference was organized by the University of Engineering and Technology, Vietnam National University, Hanoi. Besides the main track of contributed papers, this proceedings feature the results of four special sessions focusing on specific topics of interest and three invited keynote speeches. The book gathers a total of 51 carefully reviewed papers describing recent advances and development on various topics including knowledge discovery and data mining, natural language processing, expert systems, intelligent decision making, computational biology, computational modeling, optimization algorithms, and industrial applications. |
| how to build a question answering system: Natural Language Processing and Information Systems Elisabeth Métais, Farid Meziane, Vijayan Sugumaran, Warren Manning, Stephan Reiff-Marganiec, 2023-06-13 This book constitutes the refereed proceedings of the 28th International Conference on Applications of Natural Language to Information Systems, NLDB 2023, held in Derby, UK, in June 21–23, 2023 The 31 full papers and 14 short papers included in this book were carefully reviewed and selected from 89 submissions. They focus on the developments of the application of natural language to databases and information systems in the wider meaning of the term. |
| how to build a question answering system: International Conference on Computer Applications 2012 :: Volume 04 Kokula Krishna Hari K, |
| how to build a question answering system: Rough Sets and Knowledge Technology Guoyin Wang, Tianrui Li, Jerzy W. Grzymala-Busse, Duoqian Miao, Yiyu Y. Yao, 2008-05-13 This volume contains the papers selected for presentation at the Third Inter- tional Conference on Rough Sets and Knowledge Technology (RSKT 2008) held in Chengdu, P. R. China, May 16–19, 2008. The RSKT conferences were initiated in 2006 in Chongqing, P. R. China. RSKT 2007 was held in Toronto, Canada, together with RSFDGrC 2007, as JRS 2007. The RSKT conferences aim to present state-of-the-art scienti?c - sults, encourage academic and industrial interaction, and promote collaborative research in rough sets and knowledge technology worldwide. They place emphasis on exploring synergies between rough sets and knowledge discovery, knowledge management, data mining, granular and soft computing as well as emerging application areas such as bioinformatics, cognitive informatics, and Web intel- gence, both at the level of theoretical foundations and real-life applications. RSKT 2008 focused on ?ve major research ?elds: computing theory and paradigms, knowledge technology, intelligent information processing, intelligent control, and applications. This was achieved by including in the conference program sessions on rough and soft computing, rough mereology with app- cations, dominance-based rough set approach, fuzzy-rough hybridization, gr- ular computing, logical and mathematical foundations, formal concept analysis, data mining, machine learning, intelligent information processing, bioinform- ics and cognitive informatics, Web intelligence, pattern recognition, and real-life applications of knowledge technology. A very strict quality control policy was adopted in the paper review process of RSKT 2008. Firstly, the PC Chairs - viewed all submissions. |
| how to build a question answering system: Evaluating Information Retrieval and Access Tasks Tetsuya Sakai, Douglas W. Oard, Noriko Kando, 2020-09-01 This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one. |
| how to build a question answering system: Nature of Computation and Communication Phan Cong Vinh, Nguyen Huu Nhan, 2022-01-03 This book constitutes the refereed post-conference proceedings of the 7th International Conference on Nature of Computation and Communication, ICTCC 2021, held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 17 revised full papers presented were carefully selected from 43 submissions. The papers of ICTCC 2021 cover formal methods for self-adaptive systems and discuss natural approaches and techniques for natural computing systems and their applications. |
| how to build a question answering system: Intelligent Technologies for Information Analysis Ning Zhong, Jiming Liu, 2013-03-14 Intelligent Information Technology (iiT) encompasses the theories and ap plications of artificial intelligence, statistical pattern recognition, learning theory, data warehousing, data mining and knowledge discovery, Grid com puting, and autonomous agents and multi-agent systems in the context of today's as well as future IT, such as Electronic Commerce (EC), Business Intelligence (BI), Social Intelligence (SI), Web Intelligence (WI), Knowledge Grid (KG), and Knowledge Community (KC), among others. The multi-author monograph presents the current state of the research and development in intelligent technologies for information analysis, in par ticular, advances in agents, data mining, and learning theory, from both the oretical and application aspects. It investigates the future of information technology (IT) from a new intelligent IT (iiT) perspective, and highlights major iiT-related topics by structuring an introductory chapter and 22 sur vey/research chapters into 5 parts: (1) emerging data mining technology, (2) data mining for Web intelligence, (3) emerging agent technology, ( 4) emerging soft computing technology, and (5) statistical learning theory. Each chapter includes the original work of the author(s) as well as a comprehensive survey related to the chapter's topic. This book will become a valuable source of reference for R&D profession als active in advanced intelligent information technologies. Students as well as IT professionals and ambitious practitioners concerned with advanced in telligent information technologies will appreciate the book as a useful text enhanced by numerous illustrations and examples. |
| how to build a question answering system: Logic Programming Patricia M. Hill, David S. Warren, 2009-07-24 This book constitutes the refereed proceedings of the 25th International Conference on Logic Programming, ICLP 2009, held in Pasadena, CA, USA, in July2009. The 29 revised full papers together with 9 short papers, 4 invited talks, 4 invited tutorials, and the abstracts of 18 doctoral consortium articles were carefully reviewed and selected from 69 initial submissions. The papers cover all issues of current research in logic programming, namely semantic foundations, formalisms, nonmonotonic reasoning, knowledge representation, compilation, memory management, virtual machines, parallelism, program analysis, program transformation, validation and verification, debugging, profiling, concurrency, objects, coordination, mobility, higher order, types, modes, programming techniques, abductive logic programming, answer set programming, constraint logic programming, inductive logic programming, alternative inference engines and mechanisms, deductive databases, data integration, software engineering, natural language, web tools, internet agents, artificial intelligence, bioinformatics. |
| how to build a question answering system: Application of Intelligent Systems in Multi-modal Information Analytics Vijayan Sugumaran, Zheng Xu, Huiyu Zhou, 2021-04-16 This book provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. This book is a compilation of the papers presented in the 2021 International Conference on Multi-modal Information Analytics, held in Huhehaote, China, on April 23–24, 2021. |
| how to build a question answering system: The Semantic Web Harald Sack, Giuseppe Rizzo, Nadine Steinmetz, Dunja Mladenić, Sören Auer, Christoph Lange, 2016-10-19 This book constitutes the thoroughly refereed post-conference proceedings of the Satellite Events of the 13th European Conference on the Semantic Web, ESWC 2016, held in Heraklion, Greece, in May/June 2016. The volume contains 16 full papers and 38 poster and demonstration papers, carefully selected from 12 workshops focusing on specific research issues related to the Semantic Web. |
| how to build a question answering system: Advanced Multimedia and Ubiquitous Engineering James J. Park, Vincenzo Loia, Kim-Kwang Raymond Choo, Gangman Yi, 2018-11-28 This book presents the combined proceedings of the 12th International Conference on Multimedia and Ubiquitous Engineering (MUE 2018) and the 13th International Conference on Future Information Technology (Future Tech 2018), both held in Salerno, Italy, April 23 - 25, 2018. The aim of these two meetings was to promote discussion and interaction among academics, researchers and professionals in the field of ubiquitous computing technologies. These proceedings reflect the state of the art in the development of computational methods, involving theory, algorithms, numerical simulation, error and uncertainty analysis and novel applications of new processing techniques in engineering, science, and other disciplines related to ubiquitous computing. |
| how to build a question answering system: Soft Computing and Signal Processing V. Sivakumar Reddy, V. Kamakshi Prasad, Jiacun Wang, K. T. V. Reddy, 2020-03-13 This book presents selected research papers on current developments in the fields of soft computing and signal processing from the Second International Conference on Soft Computing and Signal Processing (ICSCSP 2019). The respective contributions address topics such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning, and discuss various aspects of these topics, e.g. technological considerations, product implementation, and application issues. |
| how to build a question answering system: Intelligent Systems and Sustainable Computing V. Sivakumar Reddy, V. Kamakshi Prasad, D. N. Mallikarjuna Rao, Suresh Chandra Satapathy, 2022-05-28 The book is a collection of best selected research papers presented at the International Conference on Intelligent Systems and Sustainable Computing (ICISSC 2021), held in School of Engineering, Malla Reddy University, Hyderabad, India, during 24–25 September 2021. The book covers recent research in intelligent systems, intelligent business systems, soft computing, swarm intelligence, artificial intelligence and neural networks, data mining & data warehousing, cloud computing, distributed computing, big data analytics, Internet of Things (IoT), machine learning, speech processing, sustainable high-performance systems, VLSI and embedded systems, image and video processing, and signal processing and communication. |
| how to build a question answering system: Mathematical Entity Linking Methods and Applications Philipp Scharpf, 2025-05-09 This research book explores the adaptation of traditional Entity Linking techniques to Mathematical Entity Linking (MathEL) for STEM disciplines, addressing the limitations of current Information Retrieval methods in handling mathematical expressions. By developing and evaluating novel MathEL approaches using AI, Machine Learning, and the Wikidata Knowledge Graph, significant progress is achieved in areas such as Formula Concept recognition, semantic formula search, mathematical question answering, physics exam question generation, and STEM document classification. The study also introduces a suite of open-source Wikimedia MathEL tools, including AnnoMathTeX, MathQA, and PhysWikiQuiz, designed to advance Mathematical Information Retrieval and support innovative applications in academic and educational contexts. |
| how to build a question answering system: Database Systems for Advanced Applications Matthias Renz, Cyrus Shahabi, Xiaofang Zhou, Muhammad Aamir Cheema, 2015-04-08 This two volume set LNCS 9049 and LNCS 9050 constitutes the refereed proceedings of the 20th International Conference on Database Systems for Advanced Applications, DASFAA 2015, held in Hanoi, Vietnam, in April 2015. The 63 full papers presented were carefully reviewed and selected from a total of 287 submissions. The papers cover the following topics: data mining; data streams and time series; database storage and index; spatio-temporal data; modern computing platform; social networks; information integration and data quality; information retrieval and summarization; security and privacy; outlier and imbalanced data analysis; probabilistic and uncertain data; query processing. |
| how to build a question answering system: Enterprise Information Systems Joaquim Filipe, Michał Śmiałek, Alexander Brodsky, Slimane Hammoudi, 2024-07-25 This two-volume set constitutes the refereed post-conference proceedings of the 25th International Conference on Enterprise Information Systems, ICEIS 2023, which was held in Prague, Czech Republic, during April 2023. The 41 full papers and 66 short papers presented were carefully reviewed and selected from 213 submissions. They are organized in topical sections as follows: Part One : Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; and Information Systems Analysis and Specification. Part Two : Software Agents and Internet Computing; Human-Computer Interaction; and Enterprise Architecture. |
| how to build a question answering system: Flexible Query Answering Systems Troels Andreasen, Guy De Tré, Janusz Kacprzyk, Henrik Legind Larsen, Gloria Bordogna, Sławomir Zadrożny, 2021-09-15 This book constitutes the refereed proceedings of the 14th International Conference on Flexible Query Answering Systems, FQAS 2021, held virtually and in Bratislava, Slovakia, in September 2021. The 16 full papers and 1 perspective papers presented were carefully reviewed and selected from 17 submissions. They are organized in the following topical sections: model-based flexible query answering approaches and data-driven approaches. |
| how to build a question answering system: Knowledge Graph and Semantic Computing: Knowledge Computing and Language Understanding Xiaoyan Zhu, Bing Qin, Xiaodan Zhu, Ming Liu, Longhua Qian, 2020-01-03 This book constitutes the refereed proceedings of the 4th China Conference on Knowledge Graph and Semantic Computing, CCKS 2019, held in Hangzhou, China, in August 2019. The 18 revised full papers presented were carefully reviewed and selected from 140 submissions. The papers cover wide research fields including the knowledge graph, the semantic Web, linked data, NLP, information extraction, knowledge representation and reasoning. |
| how to build a question answering system: Health Information Science Zhisheng Huang, Siuly Siuly, Hua Wang, Rui Zhou, Yanchun Zhang, 2020-10-16 This book constitutes the proceedings of the 9th International Conference on Health Information Science, HIS 2020, which took place in Amsterdam, The Netherlands, during October 20-23, 2020. The 11 full papers and 6 short papers presented in this volume were carefully reviewed and selected from 62 submissions. They were organized in topical sections named: mental health; medical record processing; medical information systems; medical diagnosis with machine learning; and health behavior and medication. |
| how to build a question answering system: NLP with Hugging Face Transformers Jason Brownlee, Muhammad Asad Iqbal Khan, 2025-05-14 Natural language processing has changed a lot recently due to the advances in language models. In the past, helping computers understand human language was a challenging task. Some primitive techniques were used, but they were not very effective. It is because human language is complex and has many nuances. This makes it difficult to model mathematically. For example, the probability model of language with a lot of exceptions would render it useless. The recent advances in transformer-based language models is not to assume anything about the language, but to ask the computer to learn from the data. In this way, you will not get a mathematically clean model. You cannot even write it down as equations. But it works very well in practice. The bloosom of trendy new applications such as ChatGPT is an evidence of this. Creating a transformer-based language model is costily. But using one is not. There are a lot of open source language models available that you can use even on your own computer. However, you must know how to use them. This includes to know what the model can do, what format of data it can accept and what it will produce, how to get the source code of the model and use it, and how to load the model weights. That’s a lot of details. This ebook gives you practical examples of how to use the most popular language models that a commodity computer can run. This uses the Hugging Face Transformers library — probably the simplest way to use the most popular language models. The ebook is not a tutorial on the library, nor how the language models work. As an NLP practitioner, neither of them is important. The focus of this ebook is to give you practical examples on what the language models can do and how to use them for a variety of NLP tasks, without knowing the detailed mechanisms behind them. |
| how to build a question answering system: Natural Language Processing and Information Retrieval Muskan Garg, Sandeep Kumar, Abdul Khader Jilani Saudagar, 2023-11-28 This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: • Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation • Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data • Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining • Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing • Covers latest datasets for natural language processing and information retrieval for social media like Twitter The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. |
| how to build a question answering system: Systematic Complex Problem Solving in the Age of Digitalization and Open Innovation Denis Cavallucci, Stelian Brad, Pavel Livotov, 2020-10-09 This book constitutes the refereed proceedings of the 20th International TRIZ Future Conference on Automated Invention for Smart Industries, TFC 2020, held in Cluj-Napoca, Romania, in October 2020 and sponsored by IFIP WG 5.4. The conference was held virtually. The 34 full papers presented were carefully reviewed and selected from 91 submissions. They are organized in the following thematic sections: computing TRIZ; education and pedagogy; sustainable development; tools and techniques of TRIZ for enhancing design; TRIZ and system engineering; TRIZ and complexity; and cross-fertilization of TRIZ for innovation management. |
| how to build a question answering system: Artificial Intelligence Enabled Management Rubee Singh, Shahbaz Khan, Anil Kumar, Vikas Kumar, 2024-06-04 Companies in developing countries are adopting Artificial Intelligence applications to increase efficiency and open new markets for their products. This book explores the multifarious capabilities and applications of AI in the context of these emerging economies and its role as a driver for decision making in current management practices. Artificial Intelligence Enabled Management argues that the economic problems facing academics, professionals, managers, governments, businesses and those at the bottom of the economic pyramid have a technical solution that relates to AI. Businesses in developing countries are using cutting-edge AI-based solutions to improve autonomous delivery of goods and services, implement automation of production and develop mobile apps for services and access to credit. By integrating data from websites, social media and conventional channels, companies are developing data management platforms, good business plans and creative business models. By increasing productivity, automating business processes, financial solutions and government services, AI can drive economic growth in these emerging economies. Public and private sectors can work together to find innovative solutions that simultaneously alleviate poverty and inequality and increase economic mobility and prosperity. The thought-provoking contributions in this book also bring attention to new barriers that have emerged in the acceptance, use, integration and deployment of AI by businesses in developing countries and explore the often-overlooked drawbacks of AI adoption that can hinder or even cause value loss. The book is a must-read for policymakers, researchers, and anyone interested in understanding the critical role of AI in the emerging economy perspective. |
| how to build a question answering system: Applied Natural Language Processing with PyTorch 2.0 Dr. Deepti Chopra, 2025-01-27 TAGLINE Unlock the Power of PyTorch 2.0 for Next-Level Natural Language Processing. KEY FEATURES ● Comprehensive coverage of NLP concepts, techniques, and best practices. ● Hands-on examples with code implementations using PyTorch 2.0. ● Focus on real-world applications and optimizing NLP models. ● Learn to develop advanced NLP solutions with dynamic GPU acceleration. DESCRIPTION Natural Language Processing (NLP) is revolutionizing industries, from chatbots to data insights. PyTorch 2.0 offers the tools to build powerful NLP models. Applied Natural Language Processing with PyTorch 2.0 provides a practical guide to mastering NLP with this advanced framework. This book starts with a strong foundation in NLP concepts and the essentials of PyTorch 2.0, ensuring that you are well-equipped to tackle advanced topics. It covers key techniques such as transformer models, pre-trained language models, sequence-to-sequence models, and more. Each chapter includes hands-on examples and code implementations for real-world application. With a focus on practical use cases, the book explores NLP tasks like sentiment analysis, text classification, named entity recognition, machine translation, and text generation. You'll learn how to preprocess text, design neural architectures, train models, and evaluate results. Whether you're a beginner or an experienced professional, this book will empower you to develop advanced NLP models and solutions. Get started today and unlock the potential of NLP with PyTorch 2.0! WHAT WILL YOU LEARN ● Master cutting-edge NLP techniques and integrate PyTorch 2.0 effectively. ● Implement NLP concepts with clear, hands-on examples using PyTorch 2.0. ● Tackle a wide range of NLP tasks, suitable for all experience levels. ● Explore tasks like sentiment analysis, text classification, and translation. ● Leverage advanced deep learning techniques for powerful NLP solutions. ● Preprocess text, design models, train, and evaluate their performance. WHO IS THIS BOOK FOR? This book is ideal for data scientists, machine learning engineers, and NLP practitioners, whether you're a beginner or an experienced professional. A basic understanding of Python and machine learning concepts is recommended, as the book focuses on practical applications, advanced techniques, and integrating PyTorch 2.0 for deep learning-powered NLP solutions. TABLE OF CONTENTS 1. Introduction to Natural Language Processing 2. Getting Started with PyTorch 3. Text Preprocessing 4. Building NLP Models with PyTorch 5. Advanced NLP Techniques with PyTorch 6. Model Training and Evaluation 7. Improving NLP Models with PyTorch 8. Deployment and Productionization 9. Case Studies and Practical Examples 10. Future Trends in Natural Language Processing and PyTorch Index |
| how to build a question answering system: Advances in Information and Communication Kohei Arai, Rahul Bhatia, 2019-02-01 This book presents a remarkable collection of chapters that cover a wide range of topics in the areas of information and communication technologies and their real-world applications. It gathers the Proceedings of the Future of Information and Communication Conference 2019 (FICC 2019), held in San Francisco, USA from March 14 to 15, 2019. The conference attracted a total of 462 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. Following a double-blind peer review process, 160 submissions (including 15 poster papers) were ultimately selected for inclusion in these proceedings. The papers highlight relevant trends in, and the latest research on: Communication, Data Science, Ambient Intelligence, Networking, Computing, Security, and the Internet of Things. Further, they address all aspects of Information Science and communication technologies, from classical to intelligent, and both the theory and applications of the latest technologies and methodologies. Gathering chapters that discuss state-of-the-art intelligent methods and techniques for solving real-world problems, along with future research directions, the book represents both an interesting read and a valuable asset. |
| how to build a question answering system: Data Integration in the Life Sciences Olivier Bodenreider, Bastien Rance, 2012-06-22 This book constitutes the refereed proceedings of the 8th International Conference on Data Integration in the Life Sciences, DILS 2012, held in College Park, MD, USA, on June 28-29, 2012. The 11 revised papers included in this volume were carefully reviewed and selected. The papers cover the following topics: foundations of data integration, new paradigms for data integration, and integrating clinical data. |
build - What exactly is 'Building'? - Stack Overflow
Feb 14, 2023 · "The build" can be done "by hand" or it can be automated, or some hybrid of the two. A manual build is a build that requires build commands like compilers to be executed one …
Build NuGet Package automatically including referenced …
below is an example project file, with PackageReferences and ProjectReferences. for the Projects they have been marked as PrivateAssets="All" and then using custom build targets to copy the …
How do I build a CMake project? - Stack Overflow
May 6, 2021 · After the configure step, you may build the project by either calling the underlying build tool (in this case, make) or by calling CMake's generic build launcher command (cmake - …
Difference between Build Solution, Rebuild Solution, and Clean …
Jun 22, 2010 · Rebuild solution will clean and then build the solution from scratch, ignoring anything it's done before. The difference between this and "Clean, followed by Build" is that …
What is the difference between npm install and npm run build?
One more thing, npm build and npm run build are two different things, npm run build will do custom work written inside package.json and npm build is a pre-defined script (not available to …
Getting msbuild.exe without installing Visual Studio
Jul 23, 2019 · Scroll down to "Tools for Visual Studio 2019" and choose "Build Tools for Visual Studio 2019" (despite the name, it's for users who don't want the full IDE) See this question for …
How to define build-args in docker-compose? - Stack Overflow
version: '3' services: node1: build: node1 image: node1 container_name: node1 node2: build: node2 image: node2 container_name: node2 I can build both images and start them with a …
build - Building vs. Compiling (Java) - Stack Overflow
Build is a compiled version of a program. Compile means, convert (a program) into a machine-code or lower-level form in which the program can be executed. In Java: Build is a Life cycle …
What is the difference between `docker-compose build` and …
May 8, 2018 · If the question here is if docker-compose build command, will build a zip kind of thing containing multiple images, which otherwise would have been built separately with usual …
How to get an environment variable value into Dockerfile during …
Mar 19, 2019 · $ docker build --build-arg request_domain=mydomain Dockerfile Note 1: Your image will not build if you have referenced an ARG in your Dockerfile but excluded it in --build …
build - What exactly is 'Building'? - Stack Overflow
Feb 14, 2023 · "The build" can be done "by hand" or it can be automated, or some hybrid of the two. A manual build is a build that requires build commands like compilers to be executed one …
Build NuGet Package automatically including referenced …
below is an example project file, with PackageReferences and ProjectReferences. for the Projects they have been marked as PrivateAssets="All" and then using custom build targets to copy the …
How do I build a CMake project? - Stack Overflow
May 6, 2021 · After the configure step, you may build the project by either calling the underlying build tool (in this case, make) or by calling CMake's generic build launcher command (cmake - …
Difference between Build Solution, Rebuild Solution, and Clean …
Jun 22, 2010 · Rebuild solution will clean and then build the solution from scratch, ignoring anything it's done before. The difference between this and "Clean, followed by Build" is that …
What is the difference between npm install and npm run build?
One more thing, npm build and npm run build are two different things, npm run build will do custom work written inside package.json and npm build is a pre-defined script (not available to …
Getting msbuild.exe without installing Visual Studio
Jul 23, 2019 · Scroll down to "Tools for Visual Studio 2019" and choose "Build Tools for Visual Studio 2019" (despite the name, it's for users who don't want the full IDE) See this question for …
How to define build-args in docker-compose? - Stack Overflow
version: '3' services: node1: build: node1 image: node1 container_name: node1 node2: build: node2 image: node2 container_name: node2 I can build both images and start them with a …
build - Building vs. Compiling (Java) - Stack Overflow
Build is a compiled version of a program. Compile means, convert (a program) into a machine-code or lower-level form in which the program can be executed. In Java: Build is a Life cycle …
What is the difference between `docker-compose build` and …
May 8, 2018 · If the question here is if docker-compose build command, will build a zip kind of thing containing multiple images, which otherwise would have been built separately with usual …
How to get an environment variable value into Dockerfile during …
Mar 19, 2019 · $ docker build --build-arg request_domain=mydomain Dockerfile Note 1: Your image will not build if you have referenced an ARG in your Dockerfile but excluded it in --build …
