Decision Support Systems Paper Appeared on a Semantic-Based Approach for Searching and Browsing Tag Spaces

DSSRecently, ECBI members Damir Vandic and dr. Flavius Frasincar published a paper on a semantic-based approach for searching and browsing tag spaces in the Decision Support Systems journal. The paper appears in volume 54, issue 1 of the prestigious journal (pages 644-654), which is ranked P in the ERIM Journals List.

In their article, Vandic and Frasincar propose the Semantic Tag Clustering Search (STCS) framework for enhancing the user experience in interacting with tagging systems. This framework consists of three parts. The first part deals with syntactic variations by finding clusters of tags that are syntactic variations of each other and assigning labels to them. The second part of the framework addresses the problem of the lack of semantics in tagging systems by recognizing contexts and constructing semantic clusters for tags. The last, and final part of the STCS framework, utilizes the clusters obtained from the first two parts to improve the search and exploration of tag spaces. For removing syntactic variations, Vandic and Frasincar use the normalized Levenshtein distance and the cosine similarity measure based on tag co-occurrences. For creating semantic clusters, two non-hierarchical and two hierarchical clustering techniques are employed. For evaluation purposes, a Web application called has been developed, which can be utilized for searching and browsing through Flickr resources.

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