Data Fusion in Information Retrieval

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...

Descripción completa

Detalles Bibliográficos
Autor principal: Wu, Shengli
Lenguaje:eng
Publicado: Springer 2012
Materias:
Engineering
Acceso en línea:https://dx.doi.org/10.1007/978-3-642-28866-1
http://cds.cern.ch/record/1488066
_version_ 1780926261221130240
author Wu, Shengli
author_facet Wu, Shengli
author_sort Wu, Shengli
collection CERN
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?
id cern-1488066
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
publisher Springer
record_format invenio
spelling cern-14880662021-04-22T00:12:06Zdoi:10.1007/978-3-642-28866-1http://cds.cern.ch/record/1488066engWu, ShengliData Fusion in Information RetrievalEngineeringThe 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?Springeroai:cds.cern.ch:14880662012
spellingShingle Engineering
Wu, Shengli
Data Fusion in Information Retrieval
title Data Fusion in Information Retrieval
title_full Data Fusion in Information Retrieval
title_fullStr Data Fusion in Information Retrieval
title_full_unstemmed Data Fusion in Information Retrieval
title_short Data Fusion in Information Retrieval
title_sort data fusion in information retrieval
topic Engineering
url https://dx.doi.org/10.1007/978-3-642-28866-1
http://cds.cern.ch/record/1488066
work_keys_str_mv AT wushengli datafusionininformationretrieval

Ejemplares similares