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Please use this identifier to cite or link to this item:
http://hdl.handle.net/1783.1/151
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| Title: | Hill climbing algorithms for content-based retrieval of similar configurations |
| Authors: | Papadias, Dimitris |
| Keywords: | MMIR
Content-based indexing
Retrieval
Image indexing
Efficient search
Non-textual information |
| Issue Date: | 2000 |
| Citation: | Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Athens, Greece, 24-28 July, 2000, ACM Press, New York, USA, 2000, p. 240-247 |
| Abstract: | The retrieval of stored images matching an input configuration is an important form of content-based retrieval. Exhaustive processing (i.e., retrieval of the best solutions) of configuration similarity queries is, in general, exponential and fast search for sub-optimal solutions is the only way to deal with the vast (and ever increasing) amounts of multimedia information in several real-time applications. In this paper we discuss the utilization of hill climbing heuristics that can provide very good results within limited processing time. We propose several heuristics, which differ on the way that they search through the solution space, and identify the best ones depending on the query and image characteristics. Finally we develop new algorithms that take advantage of the specific structure of the problem to improve performance. |
| Rights: | © ACM, 2000. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Athens, Greece, 24-28 July, 2000, ACM Press, New York, USA, 2000, p. 240-247 |
| URI: | http://hdl.handle.net/1783.1/151 |
| Appears in Collections: | CSE Conference Papers
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| sigir00.pdf | | 81Kb | Adobe PDF | View/Open |
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