Publication Date


Degree Type

Master's Project

Degree Name

Master of Science (MS)


Computer Science


Internet content is growing exponentially and searching for useful content is a tedious task that we all deal with today. Mobile phones lack of screen space and limited interaction methods makes traditional search engine interface very inefficient. As the use of mobile internet continues to grow there is a need for an effective search tool. I have created a mobile search engine that uses clustering and query expansion to find relevant web pages efficiently. Clustering organizes web pages into groups that reflect different components of a query topic. Users can ignore clusters that they find irrelevant so they are not forced to sift through a long list of off-topic web pages. Query expansion uses query results, dictionaries, and cluster labels to formulate additional terms to manipulate the original query. The new manipulated query gives a more in depth result that eliminates noise. I believe that these two techniques are effective and can be combined to make the ultimate mobile search engine.