Development of an instrument measuring user satisfaction of the human-computer interface
CHI '88 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Information retrieval: data structures and algorithms
Information retrieval: data structures and algorithms
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Modern Information Retrieval
Pruning The Vocabulary For Better Context Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Inverted files for text search engines
ACM Computing Surveys (CSUR)
Deciphering Trends in Mobile Search
Computer
A knowledge-based search engine powered by wikipedia
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
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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).