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Contributions to a Java recommender system Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_projects/rx913p97f

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  • Identifying the most relevant items in an e-commerce site is becoming more and more difficult nowadays because of the heavy overload of information. A Java Recommender System that uses Collaborative Filtering techniques has been developed to reduce such information overload and even personalize the information to the individual’s preference. The conventional recommendation provided in the earlier systems is not capable to recommend items on a specific category that the user is interested in. Recent development of a new capability in the Java Recommender System has fixed this problem. This new capability concentrates on the individual’s interests, and provides recommendations based on categories. A new CORBA API has been developed to facilitate distributed environments with different programming languages, different platforms. Finally, the correctness testing has been applied to ensure the stability of the whole system.
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  • description.provenance : Submitted by Laura Wilson (laura.wilson@oregonstate.edu) on 2012-08-06T22:52:09Z No. of bitstreams: 1 2003-32.pdf: 383190 bytes, checksum: b5b0fe7216021e61ca12c49e3117b354 (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2012-08-06T22:53:20Z (GMT) No. of bitstreams: 1 2003-32.pdf: 383190 bytes, checksum: b5b0fe7216021e61ca12c49e3117b354 (MD5)
  • description.provenance : Made available in DSpace on 2012-08-06T22:53:20Z (GMT). No. of bitstreams: 1 2003-32.pdf: 383190 bytes, checksum: b5b0fe7216021e61ca12c49e3117b354 (MD5) Previous issue date: 2003

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