Computer Science – Digital Libraries
Scientific paper
2008-05-14
Computer Science
Digital Libraries
5 pages, 2 figures
Scientific paper
Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.
Benz Dominik
Cattuto Ciro
Hotho Andreas
Stumme Gerd
No associations
LandOfFree
Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-55782