In this article we report on a study of how to use the context tree weight-ing (CTW) algorithm for lossless image compression. This algorithm has been shown to perform optimally, in terms of redundancy, for a wide class of data sources. Our study shows that this algorithm can successfully be applied to image compression even in its basic form. We also report on possible modiica-tions of the bas...

We discuss the use of probability-based natural language processing for Chinese text retrieval. We focus on comparing different text extraction methods and probabilistic weighting methods. Several document processing methods and probabilistic weighting functions are presented. A number of experiments have been conducted on large standard text collections. We present the experimental results tha...

Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles typically fall into instance-based, cluster-based, or hybrid approaches; however, most of such methods fail in discriminating among the various clusterings that participate to the ensemble. In this paper, we address th...

The context-tree weighting algorithm [4] is a universal source coding algorithm for binary tree sources. In [2] the algorithm is modified for byte-oriented tree sources. This paper describes the context-tree branch-weighting algorithm, which can reduce the number of parameters for such sources, without increasing the complexity significantly.

In text categorization, term weighting methods assign appropriate weights to the terms to improve the classification performance. In this study, we propose an effective term weighting scheme, i.e. tf.rf , and investigate several widely-used unsupervised and supervised term weighting methods on two popular data collections in combination with SVM and kNN algorithms. From our controlled experimen...

Content based labels, associated with image sequences in contemporary video indexing methods, can be textual, numerical as well as abstract, including colourhistograms and motion co-occurrence matrices. Abstract features or indices are not explicitly numeric entities but rather are composed of numeric entities. When multiple abstract features are involved, distance metrics between image sequenc...

PURPOSE Energy-resolved CT has the potential to improve the contrast-to-noise ratio (CNR) through optimal weighting of photons detected in energy bins. In general, optimal weighting gives higher weight to the lower energy photons that contain the most contrast information. However, low-energy photons are generally most corrupted by scatter and spectrum tailing, an effect caused by the limited e...

The context-tree weighting method (Willems, Shtarkov, and Tjalkens [1995]) is a sequential universal source coding method that achieves the Rissanen lower bound [1984] for tree sources. The same authors also proposed context-tree maximizing, a two-pass version of the context-tree weighting method [1993]. Later Willems and Tjalkens [1998] described a method based on ratios (betas) of sequence pr...

This paper discusses two violations of utility theory that can arise with some common multi-criteria hierarchical weighting methods when employed for selection of the best of several alternatives considering multiple criteria. First, these hierarchical weighting methods are found to violate utility theory's principle of independence of irrelevant alternatives. Proof of this violation is made by...