Experiment and Evaluation in Information Retrieval Models PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Experiment and Evaluation in Information Retrieval Models PDF full book. Access full book title Experiment and Evaluation in Information Retrieval Models by K. Latha. Download full books in PDF and EPUB format.
Author: K. Latha
Publisher: CRC Press
ISBN: 1315392607
Category : Computers
Languages : en
Pages : 378
Get Book Here
Book Description
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval
Author: K. Latha
Publisher: CRC Press
ISBN: 1315392615
Category : Computers
Languages : en
Pages : 303
Get Book Here
Book Description
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval
Author: K. Latha
Publisher: CRC Press
ISBN: 1315392607
Category : Computers
Languages : en
Pages : 378
Get Book Here
Book Description
Experiment and Evaluation in Information Retrieval Models explores different algorithms for the application of evolutionary computation to the field of information retrieval (IR). As well as examining existing approaches to resolving some of the problems in this field, results obtained by researchers are critically evaluated in order to give readers a clear view of the topic. In addition, this book covers Algorithmic Solutions to the Problems in Advanced IR Concepts, including Feature Selection for Document Ranking, web page classification and recommendation, Facet Generation for Document Retrieval, Duplication Detection and seeker satisfaction in question answering community Portals. Written with students and researchers in the field on information retrieval in mind, this book is also a useful tool for researchers in the natural and social sciences interested in the latest developments in the fast-moving subject area. Key features: Focusing on recent topics in Information Retrieval research, Experiment and Evaluation in Information Retrieval Models explores the following topics in detail: Searching in social media Using semantic annotations Ranking documents based on Facets Evaluating IR systems offline and online The role of evolutionary computation in IR Document and term clustering, Image retrieval Design of user profiles for IR Web page classification and recommendation Relevance feedback approach for Document and image retrieval
Author: Diane Kelly
Publisher: Now Publishers Inc
ISBN: 1601982240
Category : Database management
Languages : en
Pages : 246
Get Book Here
Book Description
Provides an overview and instruction on the evaluation of interactive information retrieval systems with users.
Author: Christopher D. Manning
Publisher: Cambridge University Press
ISBN: 1139472100
Category : Computers
Languages : en
Pages :
Get Book Here
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: Center for Intelligent Information Retrieval
Publisher: Springer Science & Business Media
ISBN: 0792378121
Category : Computers
Languages : en
Pages : 326
Get Book Here
Book Description
The NSF Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department of the University of Massachusetts, Amherst, in 1992. Through its efforts in basic research, applied research, and technology transfer, the CIIR has become known internationally as one of the leading research groups in the area of information retrieval. The CIIR focuses on research that results in more effective and efficient access and discovery in large, heterogeneous, distributed text and multimedia databases. The scope of the work that is done in the CIIR is broad and goes significantly beyond `traditional' areas of information retrieval such as retrieval models, cross-lingual search, and automatic query expansion. The research includes both low-level systems issues such as the design of protocols and architectures for distributed search, as well as more human-centered topics such as user interface design, visualization and data mining with text, and multimedia retrieval. Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval is a collection of papers that covers a wide variety of topics in the general area of information retrieval. Together, they represent a snapshot of the state of the art in information retrieval at the turn of the century and at the end of a decade that has seen the advent of the World-Wide Web. The papers provide overviews and in-depth analysis of theory and experimental results. This book can be used as source material for graduate courses in information retrieval, and as a reference for researchers and practitioners in industry.
Author: Karen Sparck Jones
Publisher: Butterworth-Heinemann
ISBN:
Category : Computers
Languages : en
Pages : 372
Get Book Here
Book Description
Author: Mark Sanderson
Publisher: Now Publishers Inc
ISBN: 1601983603
Category : Computers
Languages : en
Pages : 143
Get Book Here
Book Description
Use of test collections and evaluation measures to assess the effectiveness of information retrieval systems has its origins in work dating back to the early 1950s. Across the nearly 60 years since that work started, use of test collections is a de facto standard of evaluation. This monograph surveys the research conducted and explains the methods and measures devised for evaluation of retrieval systems, including a detailed look at the use of statistical significance testing in retrieval experimentation. This monograph reviews more recent examinations of the validity of the test collection approach and evaluation measures as well as outlining trends in current research exploiting query logs and live labs. At its core, the modern-day test collection is little different from the structures that the pioneering researchers in the 1950s and 1960s conceived of. This tutorial and review shows that despite its age, this long-standing evaluation method is still a highly valued tool for retrieval research.
Author: Tie-Yan Liu
Publisher: Springer Science & Business Media
ISBN: 3642142672
Category : Computers
Languages : en
Pages : 282
Get Book Here
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: Mihai Lupu
Publisher: Springer Science & Business Media
ISBN: 3642192319
Category : Computers
Languages : en
Pages : 415
Get Book Here
Book Description
Patents form an important knowledge resource –much technical information represented in patents is not represented in scientific literature – and at the same time they are important, and economically highly relevant, legal documents. Between 1998 and 2008, the number of patent applications filed yearly worldwide grew by more than 50 percent. Yet still we see a huge gap between, on the one hand, the technologies that emerged from research labs and are in use in major Internet search engines or in enterprise search systems, and, on the other hand, the systems used daily by the patent search communities. In the past few years, the editors have organized a series of events at the Information Retrieval Facility in Vienna, Austria, bringing together leading researchers in information retrieval (IR) and those who practice and use patent search, thus establishing an interdisciplinary dialogue between the IR and the intellectual property (IP) communities and creating a discursive as well as empirical space for sustainable discussion and innovation. This book is among the results of that joint effort. Many of the chapters were written jointly by IP and IR experts, while all chapters were reviewed by representatives of both communities, resulting in contributions that foster the proliferation and exchange of knowledge across fields and disciplinary mindsets. Reflecting the efforts and views of both sides of the emerging patent search research and innovation community, this is a carefully selected, organized introduction to what has been achieved, and perhaps even more significantly to what remains to be achieved. The book is a valuable resource for IR researchers and IP professionals who are looking for a comprehensive overview of the state of the art in this domain.
Author: Singh, Aarti
Publisher: IGI Global
ISBN: 1522524843
Category : Computers
Languages : en
Pages : 311
Get Book Here
Book Description
Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.
