Natural Language Data Management and Interfaces
Natural Language Data Management and Interfaces

Author: Yunyao Li

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 136

ISBN-13: 3031018621

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The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap. This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces. The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.

Natural Language Processing with Python
Natural Language Processing with Python

Author: Steven Bird

Publisher: "O'Reilly Media, Inc."

Published: 2009-06-12

Total Pages: 506

ISBN-13: 0596555717

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This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.

Natural Language Interfaces to Databases
Natural Language Interfaces to Databases

Author: Yunyao Li

Publisher: Springer Nature

Published: 2023-11-24

Total Pages: 248

ISBN-13: 3031450434

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This book presents a comprehensive overview of Natural Language Interfaces to Databases (NLIDBs), an indispensable tool in the ever-expanding realm of data-driven exploration and decision making. After first demonstrating the importance of the field using an interactive ChatGPT session, the book explores the remarkable progress and general challenges faced with real-world deployment of NLIDBs. It goes on to provide readers with a holistic understanding of the intricate anatomy, essential components, and mechanisms underlying NLIDBs and how to build them. Key concepts in representing, querying, and processing structured data as well as approaches for optimizing user queries are established for the reader before their application in NLIDBs is explored. The book discusses text to data through early relevant work on semantic parsing and meaning representation before turning to cutting-edge advancements in how NLIDBs are empowered to comprehend and interpret human languages. Various evaluation methodologies, metrics, datasets and benchmarks that play a pivotal role in assessing the effectiveness of mapping natural language queries to formal queries in a database and the overall performance of a system are explored. The book then covers data to text, where formal representations of structured data are transformed into coherent and contextually relevant human-readable narratives. It closes with an exploration of the challenges and opportunities related to interactivity and its corresponding techniques for each dimension, such as instances of conversational NLIDBs and multi-modal NLIDBs where user input is beyond natural language. This book provides a balanced mixture of theoretical insights, practical knowledge, and real-world applications that will be an invaluable resource for researchers, practitioners, and students eager to explore the fundamental concepts of NLIDBs.

Natural Language Data Management and Interfaces
Natural Language Data Management and Interfaces

Author: Yunyao Li

Publisher: Morgan & Claypool Publishers

Published: 2018-08-13

Total Pages: 158

ISBN-13: 1681734095

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The volume of natural language text data has been rapidly increasing over the past two decades, due to factors such as the growth of the Web, the low cost associated with publishing, and the progress on the digitization of printed texts. This growth combined with the proliferation of natural language systems for search and retrieving information provides tremendous opportunities for studying some of the areas where database systems and natural language processing systems overlap. This book explores two interrelated and important areas of overlap: (1) managing natural language data and (2) developing natural language interfaces to databases. It presents relevant concepts and research questions, state-of-the-art methods, related systems, and research opportunities and challenges covering both areas. Relevant topics discussed on natural language data management include data models, data sources, queries, storage and indexing, and transforming natural language text. Under natural language interfaces, it presents the anatomy of these interfaces to databases, the challenges related to query understanding and query translation, and relevant aspects of user interactions. Each of the challenges is covered in a systematic way: first starting with a quick overview of the topics, followed by a comprehensive view of recent techniques that have been proposed to address the challenge along with illustrative examples. It also reviews some notable systems in details in terms of how they address different challenges and their contributions. Finally, it discusses open challenges and opportunities for natural language management and interfaces. The goal of this book is to provide an introduction to the methods, problems, and solutions that are used in managing natural language data and building natural language interfaces to databases. It serves as a starting point for readers who are interested in pursuing additional work on these exciting topics in both academic and industrial environments.

Handbook of Research on Natural Language Processing and Smart Service Systems
Handbook of Research on Natural Language Processing and Smart Service Systems

Author: Pazos-Rangel, Rodolfo Abraham

Publisher: IGI Global

Published: 2020-10-02

Total Pages: 554

ISBN-13: 1799847314

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Natural language processing (NLP) is a branch of artificial intelligence that has emerged as a prevalent method of practice for a sizeable amount of companies. NLP enables software to understand human language and process complex data that is generated within businesses. In a competitive market, leading organizations are showing an increased interest in implementing this technology to improve user experience and establish smarter decision-making methods. Research on the application of intelligent analytics is crucial for professionals and companies who wish to gain an edge on the opposition. The Handbook of Research on Natural Language Processing and Smart Service Systems is a collection of innovative research on the integration and development of intelligent software tools and their various applications within professional environments. While highlighting topics including discourse analysis, information retrieval, and advanced dialog systems, this book is ideally designed for developers, practitioners, researchers, managers, engineers, academicians, business professionals, scholars, policymakers, and students seeking current research on the improvement of competitive practices through the use of NLP and smart service systems.

Keyword Search in Databases
Keyword Search in Databases

Author: Jeffrey Xu Yu

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 143

ISBN-13: 3031794265

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It has become highly desirable to provide users with flexible ways to query/search information over databases as simple as keyword search like Google search. This book surveys the recent developments on keyword search over databases, and focuses on finding structural information among objects in a database using a set of keywords. Such structural information to be returned can be either trees or subgraphs representing how the objects, that contain the required keywords, are interconnected in a relational database or in an XML database. The structural keyword search is completely different from finding documents that contain all the user-given keywords. The former focuses on the interconnected object structures, whereas the latter focuses on the object content. The book is organized as follows. In Chapter 1, we highlight the main research issues on the structural keyword search in different contexts. In Chapter 2, we focus on supporting structural keyword search in a relational database management system using the SQL query language. We concentrate on how to generate a set of SQL queries that can find all the structural information among records in a relational database completely, and how to evaluate the generated set of SQL queries efficiently. In Chapter 3, we discuss graph algorithms for structural keyword search by treating an entire relational database as a large data graph. In Chapter 4, we discuss structural keyword search in a large tree-structured XML database. In Chapter 5, we highlight several interesting research issues regarding keyword search on databases. The book can be used as either an extended survey for people who are interested in the structural keyword search or a reference book for a postgraduate course on the related topics. Table of Contents: Introduction / Schema-Based Keyword Search on Relational Databases / Graph-Based Keyword Search / Keyword Search in XML Databases / Other Topics for Keyword Search on Databases

The Semantic Web
The Semantic Web

Author: Karl Aberer

Publisher: Springer Science & Business Media

Published: 2007-10-22

Total Pages: 998

ISBN-13: 3540762973

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This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.

Artificial Intelligence in the Pacific Rim
Artificial Intelligence in the Pacific Rim

Author: Hozumi Tanaka

Publisher: IOS Press

Published: 1991

Total Pages: 1024

ISBN-13: 9789051990539

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In the last decade, AI firmly settled into our industrial society with the expert systems as the representative product. However, almost every one of the systems could cover only a single task domain. In the highly mechanized world of the 21st century, systems will become smart and user friendly enough to cover a wide range of task domains. Systems with much user friendliness must be multilingual because users in different domains usually have different languages. Language is formed in its own culture. Therefore, promotion for cross-cultural scientific interchange will be indispensable for the progress of AI.

Handbook of Natural Language Processing
Handbook of Natural Language Processing

Author: Robert Dale

Publisher: CRC Press

Published: 2000-07-25

Total Pages: 1015

ISBN-13: 0824746341

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This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and artificial neural networks. It emphasizes the practical tools to accommodate the selected system.

Cooperative Interfaces to Information Systems
Cooperative Interfaces to Information Systems

Author: Leonard Bolc

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 336

ISBN-13: 3642828159

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Information systems are large repositories of factual and inferential knowledge intended to be queried and maintained by a wide variety of users with different backgrounds and work tasks. The community of potential information system users is growing rapidly with advances in hardware and software technology that permit computer/communications support for more and more application areas. Unfortunately, it is often felt that progress in user interface technology has not quite matched that of other areas. Technical solutions such as computer graphics, natural language processing, or man-machine-man communications in office systems are not enough by themselves. They should be complemented by system features that ensure cooperative behavior of the interfaces, thus reducing the training and usage effort required for successful interaction. In analogy to a human dialog partner, we call an interface cooperative if it does not just accept user requests passively or answer them literally, but actively attempts to understand the users' intentions and to help them solve their applica tion problems. This leads to the central question addressed by this book: What makes an information systems interface cooperative, and how do we provide capabilities leading to cooperative interfaces? Many answers are possible. A first aspect concerns the formulation and accep tance of user requests. Many researchers assume that such requests should be formulated in natural language.