Ka Kan Lo

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In this paper, we would address a challenge faced by the legal retrieval application communities: how to build up better queries for more accurate legal information retrieval. Comparing with other retrieval applications, legal retrieval usually involves more background contexts which are documented before the retrieval process starts. This is very diierent(More)
This paper presents a framework using Encyclopedia texts to induce and generalize entities and relations existing in the corpus so that the extracted elements can be used for processing more general text. We begin with the general description of the sense model of the corpus. We then formalize the approach of automatically extracting and structuralizing(More)
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