DETECTING CORRELATIONS BETWEEN HOT DAYS IN NEWS FEEDS

Raghvendra Mall, Nahil Jain, Vikram Pudi

Abstract

We use text mining mechanisms to analyze Hot days in news feeds. We build upon the earlier work used to detect Hot topics and assume that we have already attained the Hot days. In this paper we identify the most relevant documents of a topic on a Hot day. We construct a similarity based technique for identifying and ranking these documents. Our aim is to automatically detect chains of hot correlated events over time. We develop a scheme using similarity measures like cosine similarity and KL-divergence to find correlation between these Hot days. For the ‘U.S. Presidential Elections’, the presidential debates which spanned over a week was one such event.

References

  1. Gulli, A. (2005). Ag's corpus of news articles. http://www.di.unipi.it/~gulli/AG corpus of news articles.html.
  2. Mall, R., Bagdia, N., and Pudi, V. (2009). Variations and trends in hot topics in news feeds. In Fifteenth International Conference on Management of Data.
  3. Shewart, M. and Wasson, M. (1999). Monitoring a newsfeed for hot topics. In Fifth International Conference on Knowledge Discovery in Data Mining.
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Paper Citation


in Harvard Style

Mall R., Jain N. and Pudi V. (2011). DETECTING CORRELATIONS BETWEEN HOT DAYS IN NEWS FEEDS . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 367-370. DOI: 10.5220/0003627203750378


in Bibtex Style

@conference{kdir11,
author={Raghvendra Mall and Nahil Jain and Vikram Pudi},
title={DETECTING CORRELATIONS BETWEEN HOT DAYS IN NEWS FEEDS},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={367-370},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003627203750378},
isbn={978-989-8425-79-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - DETECTING CORRELATIONS BETWEEN HOT DAYS IN NEWS FEEDS
SN - 978-989-8425-79-9
AU - Mall R.
AU - Jain N.
AU - Pudi V.
PY - 2011
SP - 367
EP - 370
DO - 10.5220/0003627203750378