On the concept of relevance in legal information retrieval

The concept of 'relevance' is crucial to legal information retrieval, but because of its intuitive understanding it goes undefined too easily and unexplored too often. We discuss a conceptual framework on relevance within legal information retrieval, based on a typology of relevance dimensions used within general information retrieval science, but tailored to the specific features of legal information. This framework can be used for the development and improvement of legal information retrieval systems

Multi-dimension diversification in legal information retrieval

The number of freely available legal data sets is increasing at high speed. Citizens can easily access a lot of information about regulations,court orders,statutes,opinions and analytical documents. Such openness brings undeniable benefits in terms of transparency,participation and availability of new services. However,legal information overload poses new challenges,especially in the field of Legal Information Retrieval. Search result diversification has gained attention as a way to increase user satisfaction in web search. We hypothesize that such a strategy will also be beneficial for search on legal data sets. We address diversification of results in legal search by introducing legal domain specific diversification criteria and adopting several state of the art methods from the web search,network analysis and text summarization domains. We evaluate our diversification framework using a real data set from the Common Law domain that we subjectively annotated with relevance judgments for this purpose. Our findings reveal that web search diversification techniques outperform other approaches (e.g. summarizationbased,graph-based methods) in the context of legal diversification,as well as that the diversity criteria we introduce provide distinctively diverse subsets of resulting documents,thus differentiating our proposal in respect to traditional diversification techniques. © Springer International Publishing AG 2016