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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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| Additional Information |
- 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 : 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
- 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)
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