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Extracting useful information from user generated text on the web is an important ongoing research in natural language processing, machine learning, and data mining. Online tools like emails, news groups, blogs, and web forums provide an effective communication platform for millions of users around the globe and also provide an added advantage of anonymity. Millions of people post information on different...
The content-based image retrieval (CBIR) system aims at searching and browsing the large image digital libraries based on automatically derived imagery features. This paper introduces two algorithms based on the normalized cut for images clustering. We extract the color and texture features for computing the distance between the images, and take advantage of the bipartition method and minimum spanning...
In the recently proposed latent perceptual indexing of audio, a collection of clips is indexed using unit-document frequency measures between a set of reference clusters as units and the clips as the documents. The reference units are derived by clustering the bag-of-feature vectors extracted from the whole audio library using an unsupervised clustering technique. Indexing is achieved through reduced-rank...
How do we identify images of the same person in photo albums? How can we find images of a particular celebrity using Web image search engines? These types of tasks require solving numerous challenging issues in computer vision including: detecting whether an image contains a face, maintaining robustness to lighting, pose, occlusion, scale, and image quality, and using appropriate distance metrics...
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