This paper targets on enhancing Latent Semantic Indexing (LSI) by exploiting category labels. Specifically, in the term-document matrix, the vector for each term either appearing in labels or semantically close to labels is scaled before performing Singular Value Decomposition (SVD) to boost its impact on the generated left singular vectors. As a result, the similarities among documents in the same category are increased. Furthermore, an adaptive scaling strategy is designed to better utilize the hierarchical structure of categories. Experimental results show that the proposed approach is able to significantly improve the performance of hierarchical text categorization.

We present an unsupervised multiscale color image segmentation algorithm. The basic idea is to apply mean shift clustering to obtain an over-segmentation and then merge regions at multiple scales to minimize the minimum description length criterion. The performance on the Berkeley segmentation benchmark campares favorably with some existing approaches.

We present an efficient color and texture segmentation algorithm by combining two statistical techniques: mean shift clustering and minimum description length (MDL) principle. Mean shift clustering is proven in generating robust and accurate segmentation results for color images, but the selection of the two scale parameters remains a challenging problem for images with texture. Optimization based on MDL principle requires little parameter tuning, but the initial input has a strong impact on its efficiency and effectiveness. Our approach is to apply mean shift clustering to generate an initial over-segmentation and then merge regions based on MDL principle. Objects with texture can be extracted with reasonable accuracy by merging regions under the guidance of MDL principle, without the need of convolving the image with a bank of filters. Experimental results on a variety of natural scene images are reported and compared with the JSEG algorithm. It takes about 1 second for our algorithm to process a 320/spl times/240 color image on a conventional PC.