We describe MuZeeker, a search engine with domain knowledge
based on Wikipedia. MuZeeker enables the user to refine a search in multiple steps by means of category selection. In the present version we focus on multimedia search related to music and we present two prototype search applications (web-based and mobile) and discuss the issues involved in
adapting the search engine for mobile phones. A category based filtering approach enables the user to refine a search through relevance feedback by category selection instead of typing additional text, which is hypothesized to be an advantage in the mobile MuZeeker application. We report from two usability experiments using the think aloud protocol, in which N=20 participants performed tasks using MuZeeker and a customized Google search engine. In both experiments web-based and mobile user interfaces were used. The experiment shows that participants are capable of solving tasks slightly better using MuZeeker, while the "inexperienced" MuZeeker users perform slightly slower than experienced Google users. This was found in both the web-based and the mobile applications. It was found that task performance in the mobile search applications (MuZeeker and Google) was 2—2.5 times lower than the corresponding web-based search applications (MuZeeker and Google).
|Title of host publication||Mobile Multimedia Processing : Fundamentals, Methods, and Applications|
|Publication status||Published - 2010|
|Series||Lecture Notes in Computer Science|
- search engine
- user interfaces