@conference {don_discovering_2007,
	title = {Discovering Interesting Usage Patterns in Text Collections: Integrating Text Mining with Visualization},
	booktitle = {Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management},
	series = {{CIKM} {\textquoteright}07},
	year = {2007},
	note = {00107},
	pages = {213{\textendash}222},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This article explores the use of computational methods - specifically text mining - for humanities research. The authors begin by arguing that, while humanities scholars use computers to access documents, they rarely use them to assist with literary interoperation or to develop research hypotheses. Text mining is wonderful for identifying patterns and searching through large bodies of text. However, the results it generate are often hard to interpret and, therefore, this method is avoided by humanities researchers. The authors of this article explore the development of a program called FeatureLens to is "designed to fill a gap by allowing users to interpret the results of the text mining thru visual exploration of the patterns in the text." FeatureLens "aims at integrating a set of text mining and visualization functionalities into a powerful tool, which provokes new insights and discoveries." By generating frequent expression lists, frequent work lists, and n-grams, FeatureLens is able to parse complicated text documents and reveal interesting patterns. },
	keywords = {digital humanities, frequent closed itemsets, n-grams, text mining, user interface},
	isbn = {978-1-59593-803-9},
	doi = {10.1145/1321440.1321473},
	url = {http://doi.acm.org/10.1145/1321440.1321473},
	author = {Don, Anthony and Zheleva, Elena and Gregory, Machon and Tarkan, Sureyya and Auvil, Loretta and Clement, Tanya and Shneiderman, Ben and Plaisant, Catherine}
}