To implement supervised Framework for Information Retrieval using Bag-of- Words Representation
نویسندگان
چکیده
The aim of this study was to implement a supervised codebook learning methodology for optimizing the feature based Bag-of-Words(Bow) representation towards data Retrieval. Following the cluster hypothesis, that states that points within the same cluster square measure seemingly to fulfill a similar data. The Bow model are often applied to different domains furthermore, so also judge our approach employing a assortment of for five time series datasets, a text dataset and a video dataset. The gains square measure three fold since the EO-Bow will improve the mean Average preciseness, whereas reducing the coding time and therefore the info storage requirements. .The Bow model treats each imageas a document that contains a number of different “visual “words. Then an image is represented as a histogram over aset of representative words, known as dictionary or codebook.These histograms describe the corresponding images andthey can be used for the subsequent retrieval tasks.
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