NDLI: An event-centric model for multilingual document similarity

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An event-centric model for multilingual document similarity

Content Provider	ACM Digital Library
Author	Gertz, Michael Strötgen, Jannik Junghans, Conny
Abstract	Document similarity measures play an important role in many document retrieval and exploration tasks. Over the past decades, several models and techniques have been developed to determine a ranked list of documents similar to a given query document. Interestingly, the proposed approaches typically rely on extensions to the vector space model and are rarely suited for multilingual corpora. In this paper, we present a novel document similarity measure that is based on events extracted from documents. An event is solely described by nearby occurrences of temporal and geographic expressions in a document's text. Thus, a document is modeled as a set of events that can be compared and ranked using temporal and geographic hierarchies. A key feature of our model is that it is term- and language-independent as temporal and geographic expressions mentioned in texts are normalized to a standard format. This also allows to determine similar documents across languages, an important feature in the context of document exploration. Our approach proves to be quite effective, including the discovery of new similarities, as our experiments using different (multilingual) corpora demonstrate.
Starting Page	953
Ending Page	962
Page Count	10
File Format	PDF
ISBN	9781450307574
DOI	10.1145/2009916.2010043
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-07-24
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Document similarity Geographic information Event extraction Temporal information
Content Type	Text
Resource Type	Article

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