NDLI: Towards more accurate and intelligent recommendation systems

Content Provider	IEEE Xplore Digital Library
Author	Kahara, T. Haataja, K. Toivanen, P.
Copyright Year	2013
Description	Author affiliation: Sch. of Comput., Univ. of Eastern Finland, Kuopio, Finland (Kahara, T.; Haataja, K.; Toivanen, P.)
Abstract	In this paper, a comparative analysis of current Recommendation Systems (RSs) is provided. In addition, we propose a new efficient Utility-Based Filtering (UBF) and Knowledge-Based Filtering (KBF) hybrid approach for calculating the utility value of each object to be recommended. The proposed system is anticipated to be at least streamlined, straightforward, and less burdening solution for recommending variety of personalized services for the user. The purpose of this paper is to help RS designers to implement more accurate and intelligent recommendation engines as well as convince them of the benefits of our new smarter system that combines best of the UBF and KBF methods, thus resulting in one unique and effective hybrid system. Moreover, some new ideas that will be used in our future research work are proposed.
Starting Page	165
Ending Page	171
File Size	380116
Page Count	7
File Format	PDF
e-ISBN	9781479935161
DOI	10.1109/ISDA.2013.6920729
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-08
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Collaborative Filtering Recommendation Systems Welding Scalability Utility-Based Filtering Noise Collaboration Content-Based Filtering Knowledge-Based Filtering
Content Type	Text
Resource Type	Article

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