The Usefulness of Dynamically Categorizing Search Results

Categorizing Search Results Using WordNet and Wikipedia

Terms used in search queries often have multiple meanings and usages. Consequently, search results corresponding to different meanings or usages may be retrieved, making identifying relevant results inconvenient and time-consuming. In this paper, we study the problem of grouping the search results based on the different meanings and usages of a query. We build on a previous work that identifies...

Dynamically Personalizing Search Results for Mobile Users

We introduce a novel situation-aware approach to personalize search results for mobile users. By providing a mobile user with appropriate information that dynamically satisfies his interests according to his situation, we tackle the problem of information overload. To build situation-aware user profile we rely on evidence issued from retrieval situations. A retrieval situation refers to the spa...

On Information Need and Categorizing Search

This dissertation is located in the area of information retrieval (IR), a discipline that deals with the task of satisfying a person’s information need with the help of a computer. IR systems let a user specify an information need, which is evaluated against large collections of digital documents. Techniques for satisfying information needs have meanwhile become ubiquitous, be it in the form of...

Categorizing Visitors Dynamically by Fast and Robust Clustering of Access Logs

Categorizing Fragments of Exemplars: Experimental and Computational Results

Analysis of the relative categorization accuracy of whole and partial items may provide deeper insight into the nature of categorization processes. I compared several logical, mathematical and computational models of categorization (including the FLMP, KRES, and variants of the GCM), and ran an experiment to get robust empirical data. The experiment showed a mixture of categorization strategies...