NDLI: Temporal Database Queries for Recommender System using Temporal Logic

Content Provider	IEEE Xplore Digital Library
Author	Zar Zar Linn Khin Haymar Saw Hla
Copyright Year	2006
Description	Author affiliation: Univ. of Comput. Studies, Yangon (Zar Zar Linn; Khin Haymar Saw Hla)
Abstract	Recommender systems (RS) use a database about user preferences to predict additional topics or products a new user might like. These conventional recommender systems make their recommendations based on the user times item information and don't take into consideration a temporal data that may be crucial in many applications. The distinguishing feature of the temporal database is time itself. When user preferences change over time, these may not be sufficient to simply recommend between users and items; the recommender systems must need to take the temporal data into consideration when recommending a new product. In this paper, we present a recommender system based on the Temporal data during a specific time that make predictions about which movie a user should like given a partial list of that user's tastes. Moreover we also present the temporal database queries and recommendations using the first order temporal logic operators
Starting Page	1
Ending Page	6
File Size	6492256
Page Count	6
File Format	PDF
ISBN	1424407176
DOI	10.1109/MHS.2006.320257
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-05
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Recommender systems Logic Motion pictures Spatial databases Multidimensional systems Context modeling Packaging Stock markets Real time systems Collaboration FOTL (First Order Temporal Logic) operators Temporal Database Recommender System
Content Type	Text
Resource Type	Article

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