In a selective information dissemination (SDI) system, users submit profiles consisting of a number of long-standing queries to represent their information needs. The system then continuously collects new documents from underlying information sources, filters them against the user profiles, and delivers relevant information to corresponding users. SDI systems are very important nowadays due to the vast amount of information that flows in the World Wide Web, as they inform users for relevant information, without requiring them to spend time to locate it. This paper presents an SDI system, which takes into account the lexical, as well as the semantic relationships between terms of documents and user profiles. In particular, a user profile is considered relevant to a document, if its terms or their synonyms or hyponyms appear in the document. The paper also presents a profile index structure supporting both the Boolean and Vector Space models.
CAiSE Short Paper Proceedings
information need,vector space model,world wide web
Semantic integration,World Wide Web,Information needs,User profile,Semantic Web Stack,Information retrieval,Computer science,Information Dissemination,Social Semantic Web,Semantic computing,Information filtering system