Dynamic similarity search in multi-metric spaces

An important research issue in multimedia databases is the retrieval of similar objects. For most applications in multi-media databases, an exact search is not meaningful. Thus, much effort has been devoted to develop efficient and effective similarity search techniques. A recent approach, that has been shown to improve the effectiveness of similarity search in multimedia databases, resorts to the usage of combinations of metrics where the desirable contribution (weight) of each metric is chosen at query time. This paper presents the Multi-Metric M-tree (M 3 -tree), a metric access method that supports similarity queries with dynamic combinations of metric functions. The M 3-tree, an extension of the M-tree, stores partial distances to better estimate the weighed distances between routing/ground entries and each query, where a single distance function is used to build the whole index. An experimental evaluation shows that the M 3-tree may be as efficient as having multiple M-trees (one for each).

[1]  Daniel A. Keim,et al.  A pivot-based index structure for combination of feature vectors , 2005, SAC '05.

[2]  Daniel A. Keim,et al.  Automatic selection and combination of descriptors for effective 3D similarity search , 2004, IEEE Sixth International Symposium on Multimedia Software Engineering.

[3]  Ricardo A. Baeza-Yates,et al.  Searching in metric spaces , 2001, CSUR.

[4]  Daniel A. Keim,et al.  Efficient geometry-based similarity search of 3D spatial databases , 1999, SIGMOD '99.

[5]  Václav Snásel,et al.  Revisiting M-Tree Building Principles , 2003, ADBIS.

[6]  Tomás Skopal,et al.  On Fast Non-metric Similarity Search by Metric Access Methods , 2006, EDBT.

[7]  Pavel Zezula,et al.  M-tree: An Efficient Access Method for Similarity Search in Metric Spaces , 1997, VLDB.

[8]  Daniel A. Keim,et al.  Using entropy impurity for improved 3D object similarity search , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).

[9]  Marco Patella,et al.  Searching in metric spaces with user-defined and approximate distances , 2002, TODS.

[10]  Martin L. Kersten,et al.  Efficient k-NN search on vertically decomposed data , 2002, SIGMOD '02.

[11]  Pavel Zezula,et al.  Similarity Search: The Metric Space Approach (Advances in Database Systems) , 2005 .

[12]  Václav Snásel,et al.  Nearest Neighbours Search Using the PM-Tree , 2005, DASFAA.

[13]  Christian Böhm,et al.  Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases , 2001, CSUR.

[14]  Daniel A. Keim,et al.  An experimental effectiveness comparison of methods for 3D similarity search , 2006, International Journal on Digital Libraries.