A hybrid CBR-IR approach to legal information retrieval

Abstract

In this paper we discuss a hybrid approach combining CaseBased Reasoning (CBR) and Information Retrieval (IR) for the retrieval of legal documents. Our hybrid CBR-IR approach takes as input a standard symbolic representation of a problem ease and retrieves texts of relevant cases from a document corpus dramatically larger than the case base available to the CBR system. Our system works by first performing a standard HYPO-style CBR anatysis and then using texts associated with certain important classes of cases found in this analysis to “seed” a modified version of INQUERY’s relevance feedback mechanism in order to generate a query. Our approach provides two benefits: it extends the reach of CBR (for retrievat purposes) to much larger corpora, and it enables the injection of knowledgebased techniques into traditional IR. We deseribe our CBRIR approach and report on on-going experiments performed in two different legal domains.