Exploring the legal discovery and enterprise tracks at the University of Iowa

Almquist, Brian
Ha-Thuc, Viet
Sehgal, Aditya K.
Arens, Robert
Srinivasan, Padmini
Faculty Advisor
information retrieval , rank aggregation
Abstract (summary)
In designing our own toolset for the TREC Legal Track, we opted to use the Lucene library of indexing and search tools. Lucene, developed in Java, is highly scalable and extendable. Indexing and searching the TREC-Legal collection proved well within Lucene’s capabilities. We indexed the entire TREC collection, opting to merge the document content and the title into a single field, using the Lucene StandardAnalyzer, which strips punctuation, but recognizes and retains elements such as e-mail addresses. The StandardAnalyzer stoplist was used for indexing. For our explorations, we converted topic fields into term vectors for querying the collection. For each topic, our system returned a ranked set of results with enough documents to match in quantity either those retrieved by a reference Boolean query executed on behalf of the TREC 2006 evaluators, or enough to reach a set cap on the number of documents returned, whichever was greater.
Publication Information
Almquist, B., Ha-Thuc, V., Sehgal, A.K., Arens, R. and Srinivasan, P. Exploring the Legal Discovery and Enterprise Tracks at the University of Iowa. Proceedings of the 16th Text REtrieval Conference (2007).
Item Type
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