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Author: Shengli Wu
Publisher: Springer Science & Business Media
ISBN: 3642288669
Category : Technology & Engineering
Languages : en
Pages : 234
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Book Description
The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others: What are the key factors that affect the performance of data fusion algorithms significantly? What conditions are favorable to data fusion algorithms? CombSum and CombMNZ, which one is better? and why? What is the rationale of using the linear combination method? How can the best fusion option be found under any given circumstances?
Author: Shengli Wu
Publisher: Springer Science & Business Media
ISBN: 3642288669
Category : Technology & Engineering
Languages : en
Pages : 234
Get Book Here
Book Description
The technique of data fusion has been used extensively in information retrieval due to the complexity and diversity of tasks involved such as web and social networks, legal, enterprise, and many others. This book presents both a theoretical and empirical approach to data fusion. Several typical data fusion algorithms are discussed, analyzed and evaluated. A reader will find answers to the following questions, among others: What are the key factors that affect the performance of data fusion algorithms significantly? What conditions are favorable to data fusion algorithms? CombSum and CombMNZ, which one is better? and why? What is the rationale of using the linear combination method? How can the best fusion option be found under any given circumstances?
Author: David E. Losada
Publisher: Springer Science & Business Media
ISBN: 3540252959
Category : Computers
Languages : en
Pages : 588
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Book Description
This book constitutes the refereed proceedings of the 27th European Conference on Information Retrieval Research, ECIR 2005, held in Santiago de Compostela, Spain in March 2005. The 34 revised full papers presented together with 2 invited keynote papers and 17 selected poster papers were carefully reviewed and selected from 124 papers submitted. The papers are organized in topical sections on peer-to-peer, information retrieval models, text summarization, information retrieval methods, text classification and fusion, user studies and evaluation, multimedia retrieval, and Web information retrieval.
Author: Lawrence A. Klein
Publisher: SPIE Press
ISBN: 9780819454355
Category : Technology & Engineering
Languages : en
Pages : 346
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Book Description
This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.
Author: Paul Clough
Publisher: Springer Science & Business Media
ISBN: 3642201601
Category : Computers
Languages : en
Pages : 821
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Book Description
This book constitutes the refereed proceedings of the 33rd annual European Conference on Information Retrieval Research, ECIR 2011, held in Dublin, Ireland, in April 2010. The 45 revised full papers presented together with 24 poster papers, 17 short papers, and 6 tool demonstrations were carefully reviewed and selected from 223 full research paper submissions and 64 poster/demo submissions. The papers are organized in topical sections on text categorization, recommender systems, Web IR, IR evaluation, IR for Social Networks, cross-language IR, IR theory, multimedia IR, IR applications, interactive IR, and question answering /NLP.
Author: Cathal Gurrin
Publisher: Springer
ISBN: 3642122752
Category : Computers
Languages : en
Pages : 696
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Book Description
These proceedings contain the papers presented at ECIR 2010, the 32nd Eu- pean Conference on Information Retrieval. The conference was organizedby the Knowledge Media Institute (KMi), the Open University, in co-operation with Dublin City University and the University of Essex, and was supported by the Information Retrieval Specialist Group of the British Computer Society (BCS- IRSG) and the Special Interest Group on Information Retrieval (ACM SIGIR). It was held during March 28-31, 2010 in Milton Keynes, UK. ECIR 2010 received a total of 202 full-paper submissions from Continental Europe (40%), UK (14%), North and South America (15%), Asia and Australia (28%), Middle East and Africa (3%). All submitted papers were reviewed by at leastthreemembersoftheinternationalProgramCommittee.Outofthe202- pers 44 were selected asfull researchpapers. ECIR has alwaysbeen a conference with a strong student focus. To allow as much interaction between delegates as possible and to keep in the spirit of the conference we decided to run ECIR 2010 as a single-track event. As a result we decided to have two presentation formats for full papers. Some of them were presented orally, the others in poster format. The presentation format does not represent any di?erence in quality. Instead, the presentation format was decided after the full papers had been accepted at the Program Committee meeting held at the University of Essex. The views of the reviewers were then taken into consideration to select the most appropriate presentation format for each paper.
Author: Marina Cocchi
Publisher: Elsevier
ISBN: 0444639853
Category : Science
Languages : en
Pages : 398
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Book Description
Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. - Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discovery - Includes comprehensible, theoretical chapters written for large and diverse audiences - Provides a wealth of selected application to the topics included
Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
ISBN: 3642142672
Category : Computers
Languages : en
Pages : 282
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Book Description
Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as collaborative filtering, definition ranking, question answering, multimedia retrieval, text summarization, and online advertisement. Leveraging machine learning technologies in the ranking process has led to innovative and more effective ranking models, and eventually to a completely new research area called “learning to rank”. Liu first gives a comprehensive review of the major approaches to learning to rank. For each approach he presents the basic framework, with example algorithms, and he discusses its advantages and disadvantages. He continues with some recent advances in learning to rank that cannot be simply categorized into the three major approaches – these include relational ranking, query-dependent ranking, transfer ranking, and semisupervised ranking. His presentation is completed by several examples that apply these technologies to solve real information retrieval problems, and by theoretical discussions on guarantees for ranking performance. This book is written for researchers and graduate students in both information retrieval and machine learning. They will find here the only comprehensive description of the state of the art in a field that has driven the recent advances in search engine development.
Author: S. Dominich
Publisher: Springer Science & Business Media
ISBN: 9401007527
Category : Computers
Languages : en
Pages : 300
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Book Description
This book offers a comprehensive and consistent mathematical approach to information retrieval (IR) without which no implementation is possible, and sheds an entirely new light upon the structure of IR models. It contains the descriptions of all IR models in a unified formal style and language, along with examples for each, thus offering a comprehensive overview of them. The book also creates mathematical foundations and a consistent mathematical theory (including all mathematical results achieved so far) of IR as a stand-alone mathematical discipline, which thus can be read and taught independently. Also, the book contains all necessary mathematical knowledge on which IR relies, to help the reader avoid searching different sources. Audience: The book will be of interest to computer or information scientists, librarians, mathematicians, undergraduate students and researchers whose work involves information retrieval.
Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Category : Computers
Languages : en
Pages :
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Book Description
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.
Author: Giambattista Amati
Publisher: Springer
ISBN: 3540714960
Category : Computers
Languages : en
Pages : 777
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Book Description
This book constitutes the refereed proceedings of the 29th annual European Conference on Information Retrieval Research, ECIR 2007, held in Rome, Italy in April 2007. The papers are organized in topical sections on theory and design, efficiency, peer-to-peer networks, result merging, queries, relevance feedback, evaluation, classification and clustering, filtering, topic identification, expert finding, XML IR, Web IR, and multimedia IR.
