NDLI: Interactive and context-aware tag spell check and correction

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Interactive and context-aware tag spell check and correction

Content Provider	ACM Digital Library
Author	Frieder, Ophir Vahabi, Hossein Bonchi, Francesco Silvestri, Fabrizio Nardini, Franco Maria
Abstract	Collaborative content creation and annotation creates vast repositories of all sorts of media, and user-defined tags play a central role as they are a simple yet powerful tool for organizing, searching and exploring the available resources. We observe that when a user annotates a resource with a set of tags, those tags are introduced one at a time. Therefore, when the fourth tag is introduced, a knowledge represented by the previous three tags, i.e., the context in which the fourth tag is produced, is available and exploitable for generating potential correction of the current tag. This context, together with the "wisdom of the crowd" represented by the co-occurrences of tags in all the resources of the repository, can be exploited to provide interactive tag spell check and correction. We develop this idea in a framework, based on a weighted tag co-occurrence graph and on nodes relatedness measures defined on weighted neighborhoods. We test our proposal on a dataset coming from YouTube. The results show that our framework is effective as it outperforms two important baselines. We also show that it is efficient, thus enabling its use in modern tagging services.
Starting Page	1869
Ending Page	1873
Page Count	5
File Format	PDF
ISBN	9781450311564
DOI	10.1145/2396761.2398534
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-10-29
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Tag spell checking and correction Tag co-occurrence graph
Content Type	Text
Resource Type	Article

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