Please use this identifier to cite or link to this item:
|Title:||Optimizing social image search with multiple criteria: Relevance, diversity, and typicality|
Social image search
|Citation:||Sun, F., Wang, M., Wang, D., Wang, X. (2012). Optimizing social image search with multiple criteria: Relevance, diversity, and typicality. Neurocomputing 95 : 40-47. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neucom.2011.05.040|
|Abstract:||The explosive growth and wide-spread accessibility of community-contributed multimedia contents on the Internet have led to a surging research activity in social image search. However, the existing tag-based search methods frequently return irrelevant or redundant results. To quickly target user's intention in the result returned by an ambiguous query, we first put forward that the top-ranked search results should meet some criteria, i.e., relevance, typicality and diversity. With the three criteria, a novel ranking scheme for social image search is proposed which incorporates both semantic similarity and visual similarity. The ranking list with relevance, typicality and diversity is returned by optimizing a measure named Average Diverse Precision. The typicality score of samples is estimated via the probability density in the space of visual features. The diversity among the top-ranked list is achieved by fusing both semantic and visual similarities of images. A comprehensive approach for calculating visual similarity is considered by fusing the similarity values according to different features. To further benefit ranking performance, a data-driven method is implemented to refine the tags of social image. Comprehensive experiments demonstrate the effectiveness of the approach proposed in this paper. © 2012 Elsevier B.V..|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on May 18, 2018
WEB OF SCIENCETM
checked on Mar 27, 2018
checked on Apr 21, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.