NDLI: Graph-of-word and TW-IDF: new approach to ad hoc IR

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Graph-of-word and TW-IDF: new approach to ad hoc IR

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Graph-of-word and TW-IDF: new approach to ad hoc IR

Content Provider	ACM Digital Library
Author	Rousseau, François Vazirgiannis, Michalis
Abstract	In this paper, we introduce novel document representation (graph-of-word) and retrieval model (TW-IDF) for ad hoc IR. Questioning the term independence assumption behind the traditional bag-of-word model, we propose a different representation of a document that captures the relationships between the terms using an unweighted directed graph of terms. From this graph, we extract at indexing time meaningful term weights (TW) that replace traditional term frequencies (TF) and from which we define a novel scoring function, namely TW-IDF, by analogy with TF-IDF. This approach leads to a retrieval model that consistently and significantly outperforms BM25 and in some cases its extension BM25+ on various standard TREC datasets. In particular, experiments show that counting the number of different contexts in which a term occurs inside a document is more effective and relevant to search than considering an overall concave term frequency in the context of ad hoc IR.
Starting Page	59
Ending Page	68
Page Count	10
File Format	PDF
ISBN	9781450322638
DOI	10.1145/2505515.2505671
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-27
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Graph-of-word Ir theory Graph-based term weighting Tw-idf Scoring functions Graph representation of document
Content Type	Text
Resource Type	Article

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