Improving collaborative filtering with multimedia indexing techniques to create user-adapting web sites

Kohrs, Arnd;Mérialdo, Bernard
MM 1999, 7th ACM International multimedia conference, October 30-November 5th, 1999, Orlando, USA

The Internet is evolving from a static collection of hypertext, to a rich assortment of dynamic services and products targeted at millions of Internet users. Formost sites it is a crucial matter to keep a close tie between the users and the site. More and more Web sites build close relationships with their users by adapting to their needs and therefore providing a personal experience. One aspect of personalization is the recommendation and presentation of information and products so that users can access the site more efficiently. However, powerful filtering technology is required in order to identify relevant items for each user. In this paper we describe how collaborative filtering and content-based filtering can be combined to provide better performance for filtering information. Filtering techniques of various nature are integrated in a weighed mix to achieve more robust results and to profit from automatic multimedia indexing technologies. The combined approach is evaluated in a prototype user-adapting Web site, the Active WebMuseum.


DOI
Type:
Conférence
City:
Orlando
Date:
1999-11-05
Department:
Data Science
Eurecom Ref:
242
Copyright:
© ACM, 1999. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in MM 1999, 7th ACM International multimedia conference, October 30-November 5th, 1999, Orlando, USA http://dx.doi.org/10.1145/319463.319467

PERMALINK : https://www.eurecom.fr/publication/242