Diversity, Assortment, Dissimilarity, Variety: A Study of Diversity Measures Using Low Level Features for Video Retrieval

In this paper we present a number of methods for re-ranking video search results in order to introduce diversity into the set of search results. The usefulness of these approaches is evaluated in comparison with similarity based measures, for the TRECVID 2007 collection and tasks [11]. For the MAP of the search results we find that some of our approaches perform as well as similarity based methods. We also find that some of these results can improve the P@N values for some of the lower N values. The most successful of these approaches was then implemented in an interactive search system for the TRECVID 2008 interactive search tasks. The responses from the users indicate that they find the more diverse search results extremely useful.

[1]  Barry Smyth,et al.  Advances in Case-Based Reasoning , 1996, Lecture Notes in Computer Science.

[2]  Zi Huang,et al.  Dissimilarity measures for content-based image retrieval , 2008, 2008 IEEE International Conference on Multimedia and Expo.

[3]  Luc Lamontagne,et al.  Case-Based Reasoning Research and Development , 1997, Lecture Notes in Computer Science.

[4]  Paul Over,et al.  TRECVID 2007--Overview , 2007, TRECVID.

[5]  Ian Soboroff,et al.  Overview of the TREC 2004 Novelty Track , 2004, TREC.

[6]  Martin Halvey,et al.  Analysis of online video search and sharing , 2007, HT '07.

[7]  Alex Ferguson,et al.  Diverse Product Recommendations Using an Expressive Language for Case Retrieval , 2002, ECCBR.

[8]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Yixin Chen,et al.  CLUE: cluster-based retrieval of images by unsupervised learning , 2005, IEEE Transactions on Image Processing.

[10]  Barry Smyth,et al.  Improving Recommendation Diversity , 2001 .

[11]  Victoria S. Uren,et al.  Comparing Dissimilarity Measures for Content-Based Image Retrieval , 2008, AIRS.

[12]  Daphna Weinshall,et al.  Classification with Nonmetric Distances: Image Retrieval and Class Representation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  Donna K. Harman,et al.  Novelty Detection: The TREC Experience , 2005, HLT.

[14]  Roelof van Zwol,et al.  Diversifying image search with user generated content , 2008, MIR '08.

[15]  David McSherry,et al.  Diversity-Conscious Retrieval , 2002, ECCBR.

[16]  George Karypis,et al.  Evaluation of Item-Based Top-N Recommendation Algorithms , 2001, CIKM '01.

[17]  Sean M. McNee,et al.  Improving recommendation lists through topic diversification , 2005, WWW '05.

[18]  Barry Smyth,et al.  Similarity vs. Diversity , 2001, ICCBR.

[19]  Kai Song,et al.  Diversifying the image retrieval results , 2006, MM '06.

[20]  Hua Li,et al.  Improving web search results using affinity graph , 2005, SIGIR '05.