Transfer non-metric measures into metric for similarity search

Similarity search is widely used in multimedia retrieval systems to find the most similar ones for a given object. Some similarity measures, however, are not metric, leading to existing metric index structures cannot be directly used. To address this issue, we propose a simulated-annealing-based technique to derive optimized mapping functions that transfer non-metric measures into metric, and still preserve the original similarity orderings. Then existing metric index structures can be used to speed up similarity search by exploiting the triangular inequality property. The experimental study confirms the efficacy of our approach. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval—Query Formulation, Retrieval Models, Search Process, Selection Process. General Terms Algorithms, Performance, Design, Experimentation. Keywords Multimedia Retrieval, Relevance Feedback, Non-metric Similarity.

• Type: Conference
• Year: 2009
• Where: MM
• Authors: Danzhou Liu, Kien A. Hua
• Keywords: Metric Index Structures, MM 2009, Multimedia, Multimedia Retrieval, Similarity Search