Data Fusion in Information Retrieval (Adaptation, Learning, and Optimization)

By: Shengli Wu (Author)

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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?

Title: Data Fusion in Information Retrieval (Adaptation, Learning, and Optimization)

Author Name: Shengli Wu (Author)

Categories: Other,

Publisher: U.S.A., Springer: 2012

ISBN Number: 3642288650

ISBN Number 13: 9783642288654

Binding: Hard Cover

Book Condition: New

Seller ID: 115507

Description: New. Data Fusion in Information Retrieval (Adaptation, Learning, and Optimization) By Shengli Wu (Author) Product Details Series: Adaptation, Learning, and Optimization (Book 13) Hardcover: 228 pages Publisher: Springer; 2012 edition (April 6, 2012) Language: English ISBN-10: 3642288650 ISBN-13: 9783642288654 Product Dimensions: 6.1 x 0.6 x 9.2 inches

Keywords: Data Fusion in Information Retrieval (Adaptation, Learning, and Optimization)