TRUCKS: A Model for Automatic Multi-Word Term Recognition.

TRUCKS: a model for automatic multi-word term recognition

A Computational Model for Recognition of Multi-font Word Images

A computational model for the recognition of multi-font machine-printed word images of highly variable quality is given. The model integrates three word recognition algorithms, each of which utilizes a diierent form of shape and context information. The approaches are character recognition based, segmentation based, and word-shape analysis based. The model overcomes limitations of previous solu...

Automatic Generation of a Multi Agent System for Crisis Management by a Model Driven Approach

Considering the increasing occurrences of unexpected events and the need for pre-crisis planning in order to reduce risks and losses, modeling instant response environments is needed more than ever. Modeling may lead to more careful planning for crisis-response operations, such as team formation, task assignment, and doing the task by teams. A common challenge in this way is that the model shou...

Rule-based Automatic Multi-word Term Extraction and Lemmatization

In this paper we present a rule-based method for multi-word term extraction that relies on extensive lexical resources in the form of electronic dictionaries and finite-state transducers for modelling various syntactic structures of multi-word terms. The same technology is used for lemmatization of extracted multi-word terms, which is unavoidable for highly inflected languages in order to pass ...

Fuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition

 In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...