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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tetali, R. Bose, J. Arif, T. |
| Copyright Year | 2013 |
| Description | Author affiliation: WMG Group, Samsung Res. Inst. India Bangalore, Bangalore, India (Tetali, R.; Bose, J.; Arif, T.) |
| Abstract | Accessing relevant information quickly, given limited time and space, is a major issue in Web browsers, especially those in mobile devices. In this paper we propose a framework for grouping similar Web documents in a browser based on similar content of the browsed pages. This grouping can help reduce clutter and enable the user to access relevant Web information quickly. The algorithm we used for clustering is MajorClust, a document similarity algorithm based on tokenizing the words in the document and then determining a cosine similarity measure to estimate the distance between the words. The entire algorithm for clustering is implemented inside the browser without the need of an external Web server. We have implemented and tested the algorithm on a mobile browser and obtained accurate finer clustering of Web pages when compared to Alexa's sub-categories. |
| Starting Page | 164 |
| Ending Page | 168 |
| File Size | 205980 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769551272 |
| DOI | 10.1109/ADCONS.2013.20 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-12-15 |
| Publisher Place | India |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Web history Document clustering MajorClust Web browser Clustering algorithms Web pages Mobile communication Mobile handsets Browsers Intelligent browsing History Engines |
| Content Type | Text |
| Resource Type | Article |
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