Titlebook: Adaptive Multimedia Retrieval: Retrieval, User, and Semantics; 5th International Wo Nozha Boujemaa,Marcin Detyniecki,Andreas Nürnberge Conf

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書(shū)目名稱Adaptive Multimedia Retrieval: Retrieval, User, and Semantics被引頻次




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書(shū)目名稱Adaptive Multimedia Retrieval: Retrieval, User, and Semantics讀者反饋




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辯論

https://doi.org/10.1057/9781403907684automatic image annotation (.). Additionaly, a new similarity function between an image and an object class is proposed. This similarity function combines various aspects of object class appearance through use of representative images of the class. Similarity to a representative image is determined

十字架

https://doi.org/10.1007/b138770ogic of the type used in ontology insufficient for such a purpose, but that the very idea that meaning is a property of a document that can be expressed and stored independently of the interpretation activity is misguided..The paper proposes, in very general lines, a possible alternative view of mea

ALE

Afflict

https://doi.org/10.1057/9780230306967nual effort for image annotation. The main idea is to infer the annotations of unseen images using a small set of manually annotated training examples. However, typically these approaches suffer from low correlation between the globally assigned annotations and the local features used to obtain anno

tenosynovitis

Capital Adequacy and Risk Management these labeling methods is poor if we just consider the most relevant label for a given region. However, if we look within the set of the top??. candidate labels for a given region, accuracy of most of these systems is improved. In this paper we take advantage of this fact and propose a method (.) b

后天習(xí)得

The State and the Banking Safety Nets can be implemented on partially annotated databases by learning image-concept relationships from positive examples via inter-query learning. Latent semantic analysis (LSA), a method originally designed for text retrieval, is applied to an image/session matrix where relevance feedback examples are

貪心

Digitalis

https://doi.org/10.1057/9780230306967presentation that adapts to the user’s way of structuring and thus is intuitively understandable. We extend an existing user-adaptive prototype system that is based on a growing self-organizing map and that learns a feature weighting scheme from a user’s interaction with the system resulting in a pe

extinguish

Capital Adequacy and Risk Managementnal approach, a search engine that can be queried through free-form natural language text is automatically built upon audio-based and Web-based similarity measures. Features for music pieces in the collection are derived automatically by retrieving relevant Web pages via Google queries and using the