This paper presents a method of optimization, based on both Bayesian Analysis technical and Gallois Lattice, of a Fuzzy Semantic Networks. The technical System we use learn by interpreting an unknown word using the links created between this new word and known words. The main link is provided by the context of the query. When novice’s query is confused with an unknown verb (goal) applied to a k...

This paper presents our ongoing effort on developing a dialogue based framework for resolving semantic interoperability in multi agent systems. Our approach is characterized by: (1) multi agent systems that have real world heterogeneous ontologies; (2) the resolution of semantic differences at run-time through an adapted ontology negotiation protocol (ONP); and (3) the use of the Word Net lexic...

intermediateand high-grade tumors; (iii) the term ‘tumor’ (neuroendocrine tumor, NET) is meant for lowto intermediate-grade neoplasms, as previously defined either ‘carcinoid’ or ‘atypical carcinoid’; (iv) the word ‘carcinoma’ (neuroendocrine carcinoma, NEC) is meant only for high-grade neoplasms, as previously defined poorly differentiated carcinomas. This terminology is adopted by the ENETS 2...

This paper aims to explore the effect of prior disambiguation on neural networkbased compositional models, with the hope that better semantic representations for text compounds can be produced. We disambiguate the input word vectors before they are fed into a compositional deep net. A series of evaluations shows the positive effect of prior disambiguation for such deep models.

Lewis Carroll's English word game Doublets is represented as a system of networks with each node being an English word and each connectivity edge confirming that its two ending words are equal in letter length, but different by exactly one letter. We show that this system, which we call the Doublets net, constitutes a complex body of linguistic knowledge concerning English word structure that h...

Many of the tasks required for semantic tagging of phrases and texts rely on a list of words annotated with some semantic features. We present a method for extracting sentiment-bearing adjectives from WordNet using the Sentiment Tag Extraction Program (STEP). We did 58 STEP runs on unique non-intersecting seed lists drawn from manually annotated list of positive and negative adjectives and eval...

The net orientation of cellulose fibrils in the outer epidermal wall of the root elongation zone of 57 angiosperm species belonging to 29 families was determined by means of Congo Red fluorescence and polarization confocal microscopy. The angiosperms can be divided in three groups. In all but four plant families, the net orientation of the cellulose fibrils is transverse to the root axis. Three...

Many of today’s web search engine users submit single word queries resulting in an imprecise and overwhelming result set. This paper describes the implementation of a query expansion application prototype, i.e., a tool to augment the original query with more, and hopefully, relevant terms. The prototype uses a semantic net to represent relationships between words and concepts used on a corporat...

The problems of e cacy estimation in noise cancelling by a neural net (LIN-Lateral Inhibition Net [5]) and the use of this information in weighting matching algorithms are focused. Since the e ect of noise on the speech signal is variable and the backpropagation training algorithm is essentially stochastic (most common patterns have more in uence in the weights re-estimation process), it is rea...

Feed forward Neural Network Language Models (NNLM) have shown consistent gains over backoff word n-gram models in a variety of tasks. However, backoff n-gram models still remain dominant in applications with real time decoding requirements as word probabilities can be computed orders of magnitude faster than the NNLM. In this paper, we present a combination of techniques that allows us to speed...