Context Modeling for Ranking and Tagging Bursty Features in Text Streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without taking into account the semantic contexts of terms, and as a result the detected bursty features may not always be interesting...
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| Main Authors: | , , , , , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2010
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/1314 https://ink.library.smu.edu.sg/context/sis_research/article/2313/viewcontent/p1769_zhao.pdf |
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| Institution: | Singapore Management University |
| Language: | English |