Options
A Comparative Study of Semantic Similarity of Tag-based Profiles
Date Issued
2009
Date
2009
Author(s)
Chang, Tsung-Chieh
Abstract
With the rapidly growing amount of information, especially in the era of Web 2.0, users experience the problem of information overload. Based on an accurate user profile, we can eliminate unwanted items and recommend the items to the user who interests. Though user profiles have been stuidied for a long time, constructing profiles based on tags is a new research topic which emerges in recent three years. Utilizing a user''s set of tags to profile the user is reasonable because tagging associates an object with a set of words which represent the semantic concepts activated by the object from the user''s perspective.owadays, Common similarity measures between profiles just consider the same attributes only. But two tags may have semantic similarity even if they are not the same tag. In this thesis, we propose semantic tag-based profiles to enrich profiles based on tag concepts we proposed. Each tag concept is built from a core tag which connects other tags holding similar semantic meanings with the core tag. Furthermore, we propose an adaptive similarity measure for semantic tag-based profiles which integrates semantic similarity between tags.ur evaluation is based on the data set crawled from Delicious, which is the most popular social bookmarking web site. The data set contains 20,578 users and 80,000 bookmarks after filtering the crawled data. From the results by empirical evaluation and user study, we show semantic tag-based profiles are better than tag-based profiles.
Subjects
tagging
profile
semantic
semantic similarity
Type
thesis
File(s)
No Thumbnail Available
Name
ntu-98-R96922008-1.pdf
Size
23.32 KB
Format
Adobe PDF
Checksum
(MD5):d1cf9db8e3185e304e9f55e013b46188