TY - CONF T1 - Discovering interesting usage patterns in text collections: integrating text mining with visualization T2 - Proceedings of the sixteenth ACM conference on Conference on information and knowledge management Y1 - 2007 A1 - Don,Anthony A1 - Zheleva,Elena A1 - Gregory,Machon A1 - Tarkan,Sureyya A1 - Auvil,Loretta A1 - Clement,Tanya A1 - Shneiderman, Ben A1 - Plaisant, Catherine KW - digital humanities KW - frequent closed itemsets KW - n-grams KW - text mining KW - user interface AB - This paper addresses the problem of making text mining results more comprehensible to humanities scholars, journalists, intelligence analysts, and other researchers, in order to support the analysis of text collections. Our system, FeatureLens1, visualizes a text collection at several levels of granularity and enables users to explore interesting text patterns. The current implementation focuses on frequent itemsets of n-grams, as they capture the repetition of exact or similar expressions in the collection. Users can find meaningful co-occurrences of text patterns by visualizing them within and across documents in the collection. This also permits users to identify the temporal evolution of usage such as increasing, decreasing or sudden appearance of text patterns. The interface could be used to explore other text features as well. Initial studies suggest that FeatureLens helped a literary scholar and 8 users generate new hypotheses and interesting insights using 2 text collections. JA - Proceedings of the sixteenth ACM conference on Conference on information and knowledge management T3 - CIKM '07 PB - ACM CY - New York, NY, USA SN - 978-1-59593-803-9 UR - http://doi.acm.org/10.1145/1321440.1321473 M3 - 10.1145/1321440.1321473 ER -