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Abstract: Event detection and tracking is a somewhat recent area of information retrieval research. The detection is about spotting new, previously unreported real-life events from online news-feed, while the tracking assigns documents to previously spotted events. We propose a new vector model consisting of four semantic classes from the documents: locations, proper names, temporal expressions and normal terms that are stored in designated subvectors. We also propose a new similarity measure based on... (Update)
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BibTeX entry: (Update)
Makkonen, J., Ahonen-Myka, H., Salmenkivi, M.: Applying semantic classes in event detection and tracking. In: Proc. International Conference on Natural Language Processing (ICON'02), Mumbai, India (2002) http://citeseer.ist.psu.edu/makkonen02applying.html More
@inproceedings{ makkonen02applying,
author = "Juha Makkonen and Helena Ahonen-Myka and Marko Salmenkivi",
title = "Applying Semantic Classes in Event Detection and Tracking",
booktitle = "Proceedings of International Conference on Natural Language Process
ing (ICON 2002)",
address = "Mumbai, India",
year = "2002",
pages = "175--183",
editor = "Rajeev Sangal and S. M. Bendre",
url = "citeseer.ist.psu.edu/makkonen02applying.html" }
Citations (may not include all citations):
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Information Retrieval
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Learning approaches for detecting and tracking news events
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