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This paper formulates the automated tagging of media as a multilabel classification problem. An induction method for creating a multilabel decision tree is presented, then applied to the problem of identifying emotions associated with music clips. The results are compared to two other multilabel classification approached (CLUS [27] and RAKEL [25]), and the(More)
In this paper, we present a computer-assisted image browsing system based on pathfinder networks. Similarity of images to one another is determined through a proposed method of automatic shape feature discovery. Local features are generated by clustering small (on the order of 10 by 10 pixels) binary image blocks culled from the edge analysis of images in(More)
Community tagging offers valuable information for media search and retrieval, but new media items are at a disadvantage. Automated tagging may populate media items with few tags, thus enabling their inclusion into search results. In this paper, a multi-label decision tree is proposed and applied to the problem of automated tagging of media data. In addition(More)
In this paper we present a vector quantization method to obtain perceptually meaningful descriptors from binary images for use in pattern recognition tasks. We introduce a distance measure and an averaging method based on the Hausdorff distance metric. Additionally we compare the proposed methods to existing Hard and Soft Centroid methods of vector(More)
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