Multi-Faceted Information Retrieval System for Large Scale Email Archives

We profile a system for search and analysis of large-scale email archives. The system builds around four facets: Content-based search engine, statistical topic model, automatically inferred social networks and time-series analysis. The facets correspond to the types of information available in email...

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Bibliographische Detailangaben
Hauptverfasser:	Perkio, Jukka, Tuulos, Ville, Buntine, Wray, Tirri, Henry
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Applied computing > Document management and text processing Data mining Data visualization Human-centered computing > Human computer interaction (HCI) > Interaction paradigms > Graphical user interfaces Information retrieval Information systems > Information retrieval Information systems > Information retrieval > Document representation Information technology Large-scale systems Mathematics of computing > Probability and statistics Power system modeling Search engines Social network services Time series analysis Web pages
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Beschreibung
Zusammenfassung:	We profile a system for search and analysis of large-scale email archives. The system builds around four facets: Content-based search engine, statistical topic model, automatically inferred social networks and time-series analysis. The facets correspond to the types of information available in email data. The presented system allows chaining or combining the facets flexibly. Results of one facet may be used as input to another, yielding remarkable combinatorial power. In information retrieval point of view, the system provides support for exploration, approximate textual searches and data visualization. We present some experimental results based on a large real-world email corpus.
DOI:	10.1109/WI.2005.103