The rapid introduction of sophisticated computers, services, telecommunications systems,
and manufacturing systems has caused a major shift in the way people use and work with …

Making obscure knowledge about matrix decompositions widely available, Understanding
Complex Datasets: Data Mining with Matrix Decompositions discusses the most common …

In this paper we present a theoretical model for understanding the performance of Latent
Semantic Indexing (LSI) search and retrieval application. Many models for understanding …

A computational model of the construction of word meaning through exposure to texts is built
in order to simulate the effects of co-occurrence values on word semantic similarities …

The Information Systems field is structured by the research topics emphasized by
communities of journals. The Latent Categorization Method categorized and automatically …

The probability that a term appears in relevant documents (P (t| R)) is a fundamental quantity
in several probabilistic retrieval models, however it is difficult to estimate without relevance …

The aim of this paper is to present a new point of view that makes it possible to give a
statistical interpretation of the traditional latent semantic analysis (LSA) paradigm based on …

This paper presents a computational model of the incremental construction of an associative
network from a corpus. It is aimed at modeling the development of the human semantic …

Topic or feature extraction is often used as an important step in document classification and
text mining. Topics are succinct representation of content in a document collection and …

As text databases increasingly become available to researchers, the limits to human
cognition are rapidly reached. Focusing on examining objective realities, this paper …