Sayan Ranu
ABSTRACT
Top-k queries find a list of k objects that have the largest scores based on some user-provided relevance function. In practice, objects in the top-k list are often similar to each other and are thus informationally redundant. This possibility of information redundancy has ignited much interest in the problem of diversity-aware top-k queries. In diversity-aware queries, the goal is to maximize the diversity of the answer set, which in turn enhances the overall information content by representing a wider spectrum of the high scoring objects. In this paper, we demonstrate that the information content in the top-k answer set can be further enhanced by favoring the representative power of the answer set instead of diversity.
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Digital Library
- G. Capannini, F. M. Nardini, R. Perego, and F. Silvestri. Efficient diversification of web search results. PVLDB, 4, 2011. Google ScholarDigital Library
- M. Drosou and E. Pitoura. Disc diversity: result diversification based on dissimilarity and coverage. PVLDB, 6(1):13--24, 2012. Google ScholarDigital Library
- DUD. http://dud.docking.org/r2/.Google Scholar
- S. Ranu, M. Hoang, and A. Singh. Answering top-k representative queries on graph databases. In SIGMOD, 2014. Google ScholarDigital Library
- S. Ranu and A. K. Singh. Answering top-k queries over a mixture of attractive and repulsive dimensions. PVLDB, 5(3):169--180, 2011. Google ScholarDigital Library
Index Terms
- Applications of Top-k Representative Queries
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