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• W35534615 abstract "This article gives an overview of the problems of information retrieval sys- tems that search court decisions. Several solutions and new research directions are suggested. The solutions are inspired by the technologies of current case-based rea- soning systems. Information retrieval(IR) concerns the retrieval of documents or information from a database of documents that satisfy a user's query. Present-day retrieval systems commonly allow users to express their query with a set of key terms, which are possibly combined with Boolean op- erators. The result of the search is a list of documents. These are usually sorted by relevance, which most of the time is simply computed as a function of the frequency of occurrence of the search terms in the documents. Searching for just the right information in legal databases is not always easy. Even database services offered by large providers such as LexisNexis and WESTLAW are not very conve- nient to use. This is because the systems on which the services run allow little more than full text retrieval augmented by keyword search on manually added subject labels. Essentially, there is no easily discoverable relationship between the text actually used and the concepts it is searched for. The decisions are written in natural language. Natural language is immensely varied. A search query and a subject in a text can be treated and expressed in a large num- ber of ways depending upon the searcher or writer and upon his context. The person who searches usually has little knowledge of the content of the database and how its documents are indexed. Basically, the searcher has to guess the words and phrases that occur in the docu- ments or that are assigned to them. When a large quantity of information is involved, subject labels - besides the huge cost of assigning them manually - are either found to be too gen- eral to be useful or too precise to be remembered by users. In addition, it is well known that searching large databases - either by a full text search or by selecting subject labels - results in a large number of potentially relevant documents, which are impossible to consult. Undoubtedly, there is a need for better retrieval models to be implemented in search en- gines of legal information systems. The aim of this article is to be an incentive for research into these retrieval models. This article starts with introducing some concepts. Then, we out- line what binds case-based reasoning and information retrieval of court decisions with regard to their common goal in information seeking, the case representations, similarity computa- tions and analogical inference. Finally, we summarize possible improvements for building retrieval systems of court decisions." @default.
• W35534615 created "2016-06-24" @default.
• W35534615 creator A5075796989 @default.
• W35534615 date "2002-01-01" @default.
• W35534615 modified "2023-09-25" @default.
• W35534615 title "What Information Retrieval Can Learn from Case-Based Reasoning" @default.
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