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Data Fusion in Information Retrieval

Data Fusion in Information Retrieval

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Adaptation, Learning, and Optimization

Data Fusion in Information Retrieval

Shengli Wu

Computers / Artificial Intelligence / General

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?


Publication Date: 09 May 2014
Publisher: Springer Berlin Heidelberg
Imprint: Springer
ISBN-13: 9783642448010
Format: Paperback softback
Page Count: 228

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