Tag Cloud Generation for Results of Multiple Keywords Queries
In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords. We adjust the state-of-the-art tag cloud generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage is more suitable for the Delicious dataset because of the different statistical properties of the dataset.
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