Context-sensitive automatic categorization of web database query results

To deal with the problem of too many answers returned from a Web database in response to a user query, this paper proposes a novel categorization approach which takes advantages of the user contextual preferences to construct a navigational tree in order to reduce the information overload. Based on the user original query, we first speculate how much the user cares about each attribute in the specified context and assign a corresponding weight to it. Then, the categorizing attribute in each level of the tree can be determined according to the weight of the attribute. The categorizing attribute for the first level of the tree is the attribute with the maximum weight. Next, we use the histogram construction algorithm to partition the values of each categories of the tree, the category with the larger exploring probability will be provided earlier to the user. Finally, the navigational tree is generated automatically and presented to the user, such that the user can easily select the relevant tuples matching his needs. Results of a preliminary user study demonstrate that our categorization method can capture the user´s preferences effectively.