Adaptive image retrieval database
A database, image technology, applied in the field of retrieval, can solve the problem of not considering user preferences and so on
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[0013] overview
[0014] As noted above, state-of-the-art CBIR (Content-Based Image Retrieval) systems do not take into account user preferences and return images that do not reflect current trends in user preferences and / or interests. These systems retrieve images without taking into account that some images are more frequently queried by users, while other images may be less frequently accessed. Additionally, user preferences and interests change over time. Images that were of interest to the user in the past may not be of interest to the user now. Furthermore, novel and new image queries cannot be incorporated into the construction of image search / retrieval algorithms. A typical example is an image query about cars. For example, most users may be interested in new car models. If a user submits a query image that includes a car, the search engine needs to sense that the user may want images of a new car model, rather than an old car model. In short, prior art image sear...
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