Dragomir Radev's Books

Natural Language Interfaces to Databases

By: Yunyao Li,Dragomir Radev,Davood Rafiei

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Natural Language Interfaces to Databases

By: Yunyao Li,Dragomir Radev,Davood Rafiei

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.

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Page Count

248

Publisher

Springer Nature

Published Date

ISBN 10

3031450434

ISBN 13

9783031450433

Graph-based Natural Language Processing and Information Retrieval

By: Rada Mihalcea,Dragomir Radev

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Graph-based Natural Language Processing and Information Retrieval

By: Rada Mihalcea,Dragomir Radev

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.

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Page Count

201

Publisher

Cambridge University Press

Published Date

ISBN 10

1139498827

ISBN 13

9781139498821

Natural Language Interfaces to Databases

By: Yunyao Li,Dragomir Radev,Davood Rafiei

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Natural Language Interfaces to Databases

By: Yunyao Li,Dragomir Radev,Davood Rafiei

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248

Publisher

Springer Nature

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ISBN 10

3031450434

ISBN 13

9783031450433

Text Mining

A Guidebook for the Social Sciences

By: Gabriel (Gabe) Ignatow,Rada F. Mihalcea

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Text Mining

A Guidebook for the Social Sciences

By: Gabriel (Gabe) Ignatow,Rada F. Mihalcea

Social media sites generate massive volumes of natural language data that are available for social science research. But social scientists have struggled to take advantage of "big data", and of the new technologies available for analyzing it. Should researchers learn programming languages in order to mine textual data? Are there software packages that can be repurposed for social science research? Can traditional theories and methods be scaled up to take advantage of new sources of textual data, or are new methods and new ways of thinking about theory needed? Text Mining: A Guidebook for Social Sciences addresses these questions and provides a methods guidebook to text mining and analysis for social scientists. It is intended for both new and experienced researchers, and provides strategic as well as practical guidance in the areas of text mining and qualitative and quantitative text analytic research methods. Gabe Ignatow and Rada Mihalcea critically survey this fast-changing landscape, providing a roadmap for researchers that will shorten the time from concept to publication, and scholarly impact.

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Page Count

208

Publisher

Sage Publications, Incorporated

Published Date

ISBN 10

148336934X

ISBN 13

9781483369341

Book's by Dragomir Radev

Natural Language Interfaces to Databases

Natural Language Interfaces to Databases

Graph-based Natural Language Processing and Information Retrieval

Graph-based Natural Language Processing and Information Retrieval

Natural Language Interfaces to Databases

Natural Language Interfaces to Databases

Text Mining

Text Mining

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