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Term proximity in document retrieval systems

Authors: Behloul Ali; Belloula Abdelkrim; Segaa Mebarek;

Term proximity in document retrieval systems

Abstract

The Automated information retrieval has appeared with the huge production of documents stored digitally, it allows you to find documents relevant to a user query formulated by keywords. The use of the neighborhood words of query can improve the relevance of research. The proposed method of representation of the documents has the advantage of integrating the information in its model of the neighborhood of terms. We evaluated our approach in terms of research relevance also the time of indexing and research. The obtained results show a remarkable improvement in the relevance due to the use of the neighborhood of the terms, and this hasn't influence on the indexing and research time that stay so quick.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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