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In this paper, we propose CYBER, a CommunitY Based sEaRch engine, for information retrieval utilizing community feedback information in a DHT network. In CYBER, each user is associated with a set of user profiles that capture his/her interests. Likewise, a document is associated with a set of profiles-one for each indexed term. A document profile is updated by users who query on the term and consider...
in both Thai and English is built for helping users from a lot of keywords of the same term and (3) a set of keywords from herbal usages can be combined with the name keyword. From the results, information collected from KUIHerb is useful for searching.
of content. The main contribution of FIRSt is an integrated strategy that enables a content-based recommender to infer user interests by applying machine learning techniques, both on official item descriptions provided by a publisher and on freely keywords which users adopt to annotate relevant items. Static content and
In this paper, we discuss semantic image annotation and propose a novel approach, called EMERGSEM, based on emergent image semantics and a recommendation system. The emergent semantics of images are derived from a generic ontology and are generated collaboratively by a group of annotators who assign keywords from a
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.