- Latest research on Data Fusion in Information Retrieval
- Includes various example applications such as developing more effective information retrieval systems, a more reliable comparison of retrieval results, the estimation of retrieval effectiveness, and world university ranking
- Written by a leading expert in the field
Buy this book
- About this book
-
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?
- Reviews
-
From the reviews:
“This book is … the result of a 10-year long engagement in data fusion within the context of various research projects. … The book is written in a very concise and dense manner, which makes it … readable for the expert, in particular the one with a good mathematical background. It contains a lot of evaluation results that help compare the various fusion methods presented, which is helpful for the practitioner. It also gives a good overview … of applications of data fusion.” (Gottfried Vossen, Zentralblatt MATH, Vol. 1246, 2012)
- Table of contents (9 chapters)
-
-
Introduction
Pages 1-5
-
Evaluation of Retrieval Results
Pages 7-18
-
Score Normalization
Pages 19-42
-
Observations and Analyses
Pages 43-71
-
The Linear Combination Method
Pages 73-116
-
Table of contents (9 chapters)
Recommended for you
Bibliographic Information
- Bibliographic Information
-
- Book Title
- Data Fusion in Information Retrieval
- Authors
-
- Shengli Wu
- Series Title
- Adaptation, Learning, and Optimization
- Series Volume
- 13
- Copyright
- 2012
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- eBook ISBN
- 978-3-642-28866-1
- DOI
- 10.1007/978-3-642-28866-1
- Hardcover ISBN
- 978-3-642-28865-4
- Softcover ISBN
- 978-3-642-44801-0
- Series ISSN
- 1867-4534
- Edition Number
- 1
- Number of Pages
- XII, 228
- Topics
