Ontology-Based Profile for Chinese Information Filtering

In the task of information filtering, the profile of the user´s interests and preferences is the key to the performance of the system. In traditional method, the profile usually represented as a set of features in the vector space model, but this kind of profile could not be satisfied by the user for lack of the semantic information. This paper proposes an approach to construct the user´s profile based on ontology described in OWL. Ontology provides a formal way to describe the domain semantics by expressing the concepts and relations between them. In our method, the features in the vector space model are defined as the instances in the ontology, and their semantic relations are represented by the means of concept-properties model. We also designed a method to compute the semantic association between the instances according to the length of their paths in the ontology graph. Then the semantic similarity of the document is calculated by the semantic association between the features. The experiment result shows that our method can achieve encouraging result