Abstract
In recent years, the employment of user feedback information to improve the image retrieval precision has become a hot subject in the research field. But in traditional relevance feedback methods, both relevant and irrelevant user assigned information was required for the retrieval system. For the sake of practicality and convenience, the present paper advances that users only need to choose their inquired image files, which generate a new index vector as relevant information. Through the feature vector space transformation, the index is moved towards the user’s inquiry intention. Meanwhile, the analysis of the user’s inquiry intention together with relevant forecast of index target in the database make it possible for the less similar vectors to get closer to the demanding vectors and thus increasing index precision. In this paper, a prototype system is introduced of image database and experimental illustration to 51138 image files. Compared with the traditional relevance feedback technique, the suggested method is shown to obviously improve the retrieval function.
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Xin, L., Ajioka, S., Shishibori, M., Kita, K. (2005). Image Feedback Retrieval Based on Vector Space Model Transformation. In: Lee, G.G., Yamada, A., Meng, H., Myaeng, S.H. (eds) Information Retrieval Technology. AIRS 2005. Lecture Notes in Computer Science, vol 3689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562382_58
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DOI: https://doi.org/10.1007/11562382_58
Publisher Name: Springer, Berlin, Heidelberg
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