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NOVEL: NO-VowEL Technique to Search Fuzzy Keyword

Authors: Amol Jaikar; Seo-Young Noh;

NOVEL: NO-VowEL Technique to Search Fuzzy Keyword

Abstract

Information retrieval techniques play vital role in the era of information technology. Inverted index is one of the technique to retrieve the information/data related with certain keyword. This technique gives faster results to retrieve relevant document from billions of documents, which contains specified keyword. In order to support wrongly spelled keyword, many techniques have been proposed including edit distance, wild-card and n-gram. The n-gram index has language-neutral and errortolerant advantage. However, it has a drawback of large size and less performance. In this paper, we have proposed NOVEL technique to search fuzzy keyword. We have implemented and tested the proposed technique on two datasets. The result shows that NOVEL technique supports not only wrongly spelled keywords, but also reduced gram size by 40-50% than K/n-gram technique. Therefore, the proposed technique is the most efficient technique to support fuzzy keyword search.

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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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