Content-based retrieval for heterogeneous domains: domain adaptation by relative aggregation points

We introduce the problem of domain adaptation for content-based retrieval and propose a domain adaptation method based on relative aggregation points (RAPs). Content-based retrieval including image retrieval and spoken document retrieval enables a user to input examples as a query, and retrieves relevant data based on the similarity to the examples. However, input examples and relevant data can be dissimilar, especially when domains from which the user selects examples and from which the system retrieves data are different. In content-based geographic object retrieval, for example, suppose that a user who lives in Beijing visits Kyoto, Japan, and wants to search for relatively inexpensive restaurants serving popular local dishes by means of a content-based retrieval system. Since such restaurants in Beijing and Kyoto are dissimilar due to the difference in the average cost and areas’ popular dishes, it is difficult to find relevant restaurants in Kyoto based on examples selected i...

• Type: Journal
• Year: 2012
• Where: SIGIR
• Authors: Makoto P. Kato, Hiroaki Ohshima, Katsumi Tanaka
• Keywords: Information Technology, Kyoto Japan, Local Dishes, SIGIR 2012, Spoken Document Retrieval