NDLI: Enabling personalization recommendation with WeightedFP for text information retrieval based on user-focus

Content Provider	IEEE Xplore Digital Library
Author	Zhenya Zhang Enhong Chen Jin Wang Xufa Wang
Copyright Year	2004
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei, China (Zhenya Zhang)
Abstract	Personalization recommendation is a valid method for lightening the user's burden on information retrieval. In order to implement personalization recommendation for text information retrieval (TR), user-focus is defined and algorithms for the construction of user-focus are given in this paper. The construction of user-focus for a user depends on his entire query requests at a period of time. Each query request of the user is treated as a transaction between TR system and him. Items in a transaction are non-noise words in the query request corresponding with the transaction. Each item is weighted with a value to measure the importance of the item for the user. Weighted frequent itemset is used for the user-focus's construction. In order to mine weighted frequented itemset fast, an algorithm named as WeightedFP is presented. The experimental result shows that the implementation of personalization recommendation based on user-focus can lighten the user's burden caused by the work of filtering valid information from vast information in some degree while time requirement of TR is satisfied well.
Sponsorship	IEEE Comput. Soc. Task Force on Information Technology for Business Application
Starting Page	272
Ending Page	276
File Size	1384128
Page Count	5
File Format	PDF
ISBN	0769521088
DOI	10.1109/ITCC.2004.1286465
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2004-04-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information retrieval Itemsets Data mining Web search Search engines Information filtering Computer science Information filters Internet Web sites
Content Type	Text
Resource Type	Article

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