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Title:
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APPLYING CLUSTERING TO THE LOG ANALYSIS OF RICH INTERNET APPLICATIONS FOR USABILITY EVALUATION |
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Author(s):
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Alana Regina Biagi Silva Lisboa, Adriano Rivolli, Luciano Tadeu Esteves Pansanato |
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ISBN:
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978-989-8533-24-1 |
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Editors:
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Pedro Isaías and Bebo White |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Usability evaluation, rich internet application, user interaction, log analysis, clustering. |
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Type:
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Full Paper |
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First Page:
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27 |
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Last Page:
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34 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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This paper presents an application of clustering to the log analysis of user interaction with Rich Internet Applications for usability evaluation. The proposed approach is novel because it uses logs with detailed information about the user interaction with a web application and not only the information obtained from server log files. In Rich Internet Applications, as great part of the interface processing occurs in the client, data stored in the server on user interaction are insufficient to extract detailed information on the real use of the application. In this work, a tool called Web Application Usage Tracking Tool, WAUTT, is used to get detailed information at the level of the page elements and events associated to the user interaction with a web application. A preprocessing of the collected data was performed to apply a clustering algorithm. The k-means algorithm was used to cluster the logs with similar patterns of behavior. The advantage of applying clustering is the reduction of instances which should be analyzed in a usability evaluation supported by log analysis. |
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