2013 ExploratoryAnalysisofHighlyHete

• (Maiya et al., 2013) ⇒ Arun S. Maiya, John P. Thompson, Francisco Loaiza-Lemos, and Robert M. Rolfe. (2013). “Exploratory Analysis of Highly Heterogeneous Document Collections.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2488195

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Exploratory+Analysis+of+Highly+Heterogeneous+Document+Collections
• http://dl.acm.org/citation.cfm?id=2487575.2488195&preflayout=flat#citedby

Quotes

Author Keywords

• Faceted browsing; faceted navigation; information filtering; keyphrase extraction; machine learning; natural language; tag clouds; text analysis; topic modeling

Abstract

We present an effective multifaceted system for exploratory analysis of highly heterogeneous document collections. Our system is based on intelligently tagging individual documents in a purely automated fashion and exploiting these tags in a powerful faceted browsing framework. Tagging strategies employed include both unsupervised and supervised approaches based on machine learning and natural language processing. As one of our key tagging strategies, we introduce the KERA algorithm (Keyword Extraction for Reports and Articles). KERA extracts topic-representative terms from individual documents in a purely unsupervised fashion and is revealed to be significantly more effective than state-of-the-art methods. Finally, we evaluate our system in its ability to help users locate documents pertaining to military critical technologies buried deep in a large heterogeneous sea of information.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 ExploratoryAnalysisofHighlyHete	Arun S. Maiya John P. Thompson Francisco Loaiza-Lemos Robert M. Rolfe			Exploratory Analysis of Highly Heterogeneous Document Collections				10.1145/2487575.2488195		2013