Rather than analyzing the worst case performance of algorithms, one can investigate their performance on typical instances of a given size. This is the approach we investigate in this paper. Of course, the first question we must answer is: what do we mean by a typical instance of a given size? Sometimes, there is a natural answer to this question. For example, in developing an algorithm which i...

Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two{mode and co-occurrence data, which has applications in information retrieval and ltering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Semantic Analysis which stems from linear algebra and performs a Singular Value Decomposition of co-occu...

Comparative string data has proven to be a valuable resource for improving the accuracy of computational methods for string analysis. In this report we describe the characteristics of comparative string data, focusing on biological sequences, and natural language text. We then describe a general probabilistic framework for analyzing pairs of strings, show how posterior based methods can be used...

The method based on local features has an advantage that the important local motion feature is represented as bag-of-features, but lacks the location information. Additionally, in order to employ an approach based on bag-of-features, language models represented by pLSA and LDA (Latent Dirichlet Allocation) have to be applied to. These are unsupervised learning, but they require the number of la...

This paper describes experimentswith a PLSA-based language model for conversational telephone speech. This model uses a long-range history and exploits topic information in the test text to adjust probabilities of test words. The PLSA-based model was found to lower test set perplexity over a traditional word+class-based -gram by 13% (optimistic estimate using a reference transcript as history) ...

Classification is one of the most important tasks in data mining and, nowadays, has been applied to solve problems related to different areas, such as administration, finance, education, health and others. Therefore, the construction of precise and computationally efficient classifiers is a relevant challenge in data mining field. In previous works we presented an efficient method for protein c...

Abstract. The modern unification of the European standards EUROCODE requires securing a constant quality of metallurgical production in the EU countries. In this paper, experimentally found statistical characteristics of yield stress, ultimate tensile strength and ductility of Czech and Austrian steel are presented. In the probabilistic reliability analysis, the experimentally found yield stres...

A precise analysis of the retrieval of signature trees is presented. A signature tree is a data structure constructed over a signature file to speed up searching all those signatures, which match a given query signature. The methods used include a detailed study of probabilistic analysis in conjunction with suitable contour integration of complex variabled functions. © 2006 Elsevier B.V. All ri...

An integrated method for bilingual chunk partition and alignment, called “Interactional Matching”, is proposed in this paper. Different from former works, our method tries to get as necessary information as possible from the bilingual corpora themselves, and through bilingual constraint it can automatically build one-to-one chunk-pairs associated with the chunk-pair confidence coefficients. Als...

We analyze the unit-demand Euclidean vehicle routeing problem, where n customers are modeled as independent, identically distributed uniform points and have unit demand. We show new lower bounds on the optimal cost for the metric vehicle routeing problem and analyze them in this setting. We prove that there exists a constant ĉ > 0 such that the iterated tour partitioning heuristic given by Haim...