From Word Sense Disambiguation to Semantic Regularities – This work is presented in this paper focusing on the problem of word sense extraction. Our main idea is to extract the meaning with proper meanings from the sense’s semantic relations and the word sense itself. Since the meanings of the words are defined by the word sense, and so it is impossible for the meaning of a word sense to be extracted by the word sense without an intermediate word sense, a word sense can be extracted by a word sense in a sense. In this paper a new method is proposed for extracting the meaning of words based on the semantic relations and the word sense itself; the purpose of this paper is to propose an efficient and efficient method for extracting the meaning of words. The method is applied to the problem of word sense extraction from a given source sentence.

This paper presents a methodology for identifying user interests and preferences for user-generated content in Internet articles. We start by evaluating the impact of topics in user-generated articles in terms of articles’ relevance to users’ interests, and a quantitative study of this impact would be useful to facilitate user exploration of Internet articles.

A Fast Convex Formulation for Unsupervised Model Selection on Graphs

Rationalization: A Solved Problem with Rational Probabilities?

From Word Sense Disambiguation to Semantic Regularities

A survey of perceptual-motor training

A Framework for Interpretable Machine Learning of Web Usage DataThis paper presents a methodology for identifying user interests and preferences for user-generated content in Internet articles. We start by evaluating the impact of topics in user-generated articles in terms of articles’ relevance to users’ interests, and a quantitative study of this impact would be useful to facilitate user exploration of Internet articles.