{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:17Z","timestamp":1740202037743,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009]]},"abstract":"<jats:p>Image retrieval by using content analysis is known as a difficult task. In our previous studies [1] and [2] mixed-metrics were proposed in order to combine color and texture metrics for image retrieval task. It was shown that it is always possible to mark out the best mixed-metrics for every group of similar images and improve retrieval effectiveness. In order to get the proper mixed-metrics a particular query-image should be classified to one of the predefined groups of perceptually similar images and this should be done in the real-time mode while processing the query and retrieving the result. In our previous work [3] the highly specialized classification method was proposed to solve this task. In the current study Naive Bayes and SVM classifiers are discussed and applied to the mixed-metrics approach to image retrieval. Classification result for these classifiers in comparison with the classifier, proposed in [3], are presented.<\/jats:p>","DOI":"10.3233\/978-1-58603-939-4-281","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:05Z","timestamp":1740133625000},"source":"Crossref","is-referenced-by-count":0,"title":["Query Classification in Content-Based Image Retrieval"],"prefix":"10.3233","author":[{"family":"Markov Ilya","sequence":"additional","affiliation":[]},{"family":"Vassilieva Natalia","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Databases and Information Systems V"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:02:55Z","timestamp":1740135775000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=187&spage=281"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-58603-939-4-281","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2009]]}}}