NDLI: Collaborative Feature-Combination Recommender Exploiting Explicit and Implicit User Feedback

Content Provider	IEEE Xplore Digital Library
Author	Zanker, M. Jessenitschnig, M.
Copyright Year	2009
Abstract	Collaborative filtering (CF) is currently the most popular technique used in commercial recommender systems. Algorithms of this type derive personalized product propositions for customers by exploitingstatistics derived from vast amounts of transaction data.Traditionally, basic CF algorithms have exploited a single category of ratings despite the fact that on many platforms a variety of different forms of user feedback are available for personalization and recommendation. In this paper we explore a collaborative feature-combination algorithm that concurrently exploits multiple aspects of the user model like clickstream data, sales transactions and explicit user requirements to overcome some known shortcomingsof CF like the cold-start problem for new users. We validate our contribution by evaluating it against the standard user-to-user CF algorithm using a dataset from a commercial Web shop. Evaluation results indicate considerable improvements in terms of user coverageand accuracy.
Starting Page	49
Ending Page	56
File Size	203302
Page Count	8
File Format	PDF
ISBN	9780769537559
ISSN	15301354
DOI	10.1109/CEC.2009.84
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-20
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	cold-start problem Navigation Information filtering hybrid recommendation methods Collaborative filtering Feedback Collaboration Information filters Marketing and sales Intelligent systems Informatics Recommender systems Business
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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