This paper proposes word clustering using word embedding. We used a neural net-based continuous skip-gram method for generating word embedding in continuous space. The proposed word clustering method represents each word in the vector space using a neural network. The K-means clustering method partitions word embedding into predetermined K-word

A finite word is called Petri net solvable if it is isomorphic to the reachability graph of some unlabelled Petri net. In this paper, the class of two-letter Petri net solvable words is studied.

Prof. Carl Adam Petri wrote: “In order to apply net theory with success, a user of net theory can just rely on the fact that every net which he can specify explicitly (draw on paper) can be connected by a short (≤ 4) chain of net morphisms to the physical real word; your net is, in a very precise sense, physically implementable.” (Status Report On Net Theory, 1989, a forward for my book Petri N...

A novel method based on Wikipedia for clustering keyword of reviews is proposed. Users can quickly finding the themes they interest through it. First the method extracts keywords, then calculates word similarity based on Wikipedia to generate similarity matrix, finally uses k-means to cluster. The performance is better than the methods which based on How-net and Word-net. The accuracy is around...

This paper introduces an algorithm for automatically acquiring the conceptual structure of each word from corpus. The concept of a word is defined within the probabilistic framework. A variation of Belief Net named as Collocation Map is used to compute the probabilities. The Belief Net captures the conditional independences of words, which is obtained from the cooccurrence relations. The comput...

Problem statement: This study attempts to present an object-net method for word sense disambiguation. It is proposed to model the elementary meanings which assist the machine to autonomously undertake the analysis and synthesis processes of meaning. Approach: In the proposed methodology, the disambiguation process was performed in context manner. Starting from natural text, the context of the s...

In this paper I present a number of studies of individual lexical items demonstrating the incredible variety of idiosyncratic properties that occur in the lexicon of English. While many current theories ignore this level of detail, I argue that a complete on-line lexicon suitable for a variety of linguistic and computational uses must include much more information than is available in any exist...

A three layer back propagation neural net is set up to determine the dependence between the semantic class of a bisyllabic Chinese word and its two characters. Simulations were performed using a three–layer back–propagation neural net (BPNN) with various combinations of inputs. The inputs are (1) semantic classes of the characters, (2) Entropy of the characters and (3) semantic strengths [1] of...