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Probabilistic Topic Models For Information Retrieval And Concept Modeling


Probabilistic Topic Models For Information Retrieval And Concept Modeling
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Probabilistic Topic Models For Information Retrieval And Concept Modeling


Probabilistic Topic Models For Information Retrieval And Concept Modeling
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Author : Chaitanya Chandra Chemudugunta
language : en
Publisher:
Release Date : 2009

Probabilistic Topic Models For Information Retrieval And Concept Modeling written by Chaitanya Chandra Chemudugunta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.


Statistical topic models are a class of probabilistic latent variable models for textual data that represent text documents as distributions over topics. These models have been shown to produce interpretable summarization of documents in the form of topics. In this dissertation, we investigate how the statistical topic modeling framework can be used for information retrieval tasks and for the integration of background knowledge in the form of semantic concepts. We first describe the special-words topic models in which a document is represented as a distribution of (i) a mixture of shared topics, (ii) a special-words distribution specific to the document, and (iii) a corpus-level background distribution. We describe the utility of the special-words topic models for information retrieval tasks and illustrate a variation of the model for metadata enhancement of digital libraries with multiple corpora. We next investigate the problem of integrating background knowledge in the form of semantic concepts into the topic modeling framework. To combine data-driven topics and semantic concepts, we propose the concept-topic model which represents a document as a distribution over data-driven topics and semantic concepts. We extend this model to the hierarchical concept-topic model to incorporate concept hierarchies into the modeling framework. For all these models, we develop learning algorithms and demonstrate their utility with experiments conducted on real-world data sets.



Advances In Information Retrieval


Advances In Information Retrieval
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Author : Pavel Serdyukov
language : en
Publisher: Springer
Release Date : 2013-03-12

Advances In Information Retrieval written by Pavel Serdyukov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-12 with Computers categories.


This book constitutes the proceedings of the 35th European Conference on IR Research, ECIR 2013, held in Moscow, Russia, in March 2013. The 55 full papers, 38 poster papers and 10 demonstrations presented in this volume were carefully reviewed and selected from 287 submissions. The papers are organized in the following topical sections: user aspects; multimedia and cross-media IR; data mining; IR theory and formal models; IR system architectures; classification; Web; event detection; temporal IR, and microblog search. Also included are 4 tutorial and 2 workshop presentations.



Statistical Language Models For Information Retrieval


Statistical Language Models For Information Retrieval
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Author : Chengxiang Zhai
language : en
Publisher: Springer Nature
Release Date : 2022-05-31

Statistical Language Models For Information Retrieval written by Chengxiang Zhai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.


As online information grows dramatically, search engines such as Google are playing a more and more important role in our lives. Critical to all search engines is the problem of designing an effective retrieval model that can rank documents accurately for a given query. This has been a central research problem in information retrieval for several decades. In the past ten years, a new generation of retrieval models, often referred to as statistical language models, has been successfully applied to solve many different information retrieval problems. Compared with the traditional models such as the vector space model, these new models have a more sound statistical foundation and can leverage statistical estimation to optimize retrieval parameters. They can also be more easily adapted to model non-traditional and complex retrieval problems. Empirically, they tend to achieve comparable or better performance than a traditional model with less effort on parameter tuning. This book systematically reviews the large body of literature on applying statistical language models to information retrieval with an emphasis on the underlying principles, empirically effective language models, and language models developed for non-traditional retrieval tasks. All the relevant literature has been synthesized to make it easy for a reader to digest the research progress achieved so far and see the frontier of research in this area. The book also offers practitioners an informative introduction to a set of practically useful language models that can effectively solve a variety of retrieval problems. No prior knowledge about information retrieval is required, but some basic knowledge about probability and statistics would be useful for fully digesting all the details. Table of Contents: Introduction / Overview of Information Retrieval Models / Simple Query Likelihood Retrieval Model / Complex Query Likelihood Model / Probabilistic Distance Retrieval Model / Language Models for Special Retrieval Tasks / Language Models for Latent Topic Analysis / Conclusions



Information Retrieval Technology


Information Retrieval Technology
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Author : Dawei Song
language : en
Publisher: Springer
Release Date : 2009-09-30

Information Retrieval Technology written by Dawei Song and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-30 with Computers categories.


This book constitutes the refereed proceedings of the 5th Asia Information Retrieval Symposium, AIRS 2009, held in Sapporo, Japan, in October 2009. The 18 revised full papers and 20 revised poster papers presented were carefully reviewed and selected from 82 submissions. All current aspects of information retrieval - in theory and practice - are addressed; working with text, audio, image, video and multimedia data.



Handbook Of Latent Semantic Analysis


Handbook Of Latent Semantic Analysis
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Author : Thomas K. Landauer
language : en
Publisher: Psychology Press
Release Date : 2007-02-15

Handbook Of Latent Semantic Analysis written by Thomas K. Landauer and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-02-15 with Psychology categories.


The Handbook of Latent Semantic Analysis is the authoritative reference for the theory behind Latent Semantic Analysis (LSA), a burgeoning mathematical method used to analyze how words make meaning, with the desired outcome to program machines to understand human commands via natural language rather than strict programming protocols. The first book



Probabilistic Topic Models


Probabilistic Topic Models
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Author : Di Jiang
language : en
Publisher: Springer Nature
Release Date : 2023-06-08

Probabilistic Topic Models written by Di Jiang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-08 with Computers categories.


This book introduces readers to the theoretical foundation and application of topic models. It provides readers with efficient means to learn about the technical principles underlying topic models. More concretely, it covers topics such as fundamental concepts, topic model structures, approximate inference algorithms, and a range of methods used to create high-quality topic models. In addition, this book illustrates the applications of topic models applied in real-world scenarios. Readers will be instructed on the means to select and apply suitable models for specific real-world tasks, providing this book with greater use for the industry. Finally, the book presents a catalog of the most important topic models from the literature over the past decades, which can be referenced and indexed by researchers and engineers in related fields. We hope this book can bridge the gap between academic research and industrial application and help topic models play an increasingly effective role in both academia and industry. This book offers a valuable reference guide for senior undergraduate students, graduate students, and researchers, covering the latest advances in topic models, and for industrial practitioners, sharing state-of-the-art solutions for topic-related applications. The book can also serve as a reference for job seekers preparing for interviews.



International Conference On Innovative Computing And Communications


International Conference On Innovative Computing And Communications
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Author : Deepak Gupta
language : en
Publisher: Springer Nature
Release Date : 2020-07-30

International Conference On Innovative Computing And Communications written by Deepak Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-30 with Technology & Engineering categories.


This book includes high-quality research papers presented at the Third International Conference on Innovative Computing and Communication (ICICC 2020), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on 21–23 February, 2020. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.



Introduction To Information Retrieval


Introduction To Information Retrieval
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Author : Christopher D. Manning
language : en
Publisher: Cambridge University Press
Release Date : 2008-07-07

Introduction To Information Retrieval written by Christopher D. Manning and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-07 with Computers categories.


Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.



Mining Text Data


Mining Text Data
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03

Mining Text Data written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-03 with Computers categories.


Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.



Two Day International Conference On Data Science And Information Ecosystem 21


Two Day International Conference On Data Science And Information Ecosystem 21
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Author : Dr.M.Thangaraj
language : en
Publisher: Shanlax Publications
Release Date :

Two Day International Conference On Data Science And Information Ecosystem 21 written by Dr.M.Thangaraj and has been published by Shanlax Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.