DocumentCode :
1694146
Title :
Condorcet Fusion for Blog Opinion Retrieval
Author :
Wu, Shengli ; Zeng, Xiaoqin
Author_Institution :
Sch. of Comput. & Telecommun., Jiangsu Univ., Zhenjiang, China
fYear :
2012
Firstpage :
156
Lastpage :
160
Abstract :
Blogs have been popular social networking platforms in recent years. Blog opinion retrieval is one of the key issues that needs to be solved. In this paper, we investigate if the Condorcet fusion and the weighted Condorcet fusion can be used for effectiveness improvement of blog opinion retrieval. The experiments carried out with the data set from the TREC 2008 Blog track show that the Condorcet fusion is effective and the weighted Condorcet fusion, with its weights trained by linear discriminant analysis, is very effective. Both of them outperform the best component result by a clear margin.
Keywords :
information retrieval; search engines; sensor fusion; social networking (online); statistical analysis; TREC 2008 Blog track; blog opinion retrieval; data set; linear discriminant analysis; search engines; social networking platforms; weighted Condorcet fusion; Analytical models; Blogs; Educational institutions; Training; USA Councils; condorcet fusion; data fusion; information retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Database and Expert Systems Applications (DEXA), 2012 23rd International Workshop on
Conference_Location :
Vienna
ISSN :
1529-4188
Print_ISBN :
978-1-4673-2621-6
Type :
conf
DOI :
10.1109/DEXA.2012.23
Filename :
6327419
Link To Document :
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