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Focusing on the defects existing in classical Association Rules Mining algorithms, we explore a new way of mining temporal association rules with the time-property in dataset. By combining with the Rough Set Theory and parallel computing technology, a temporal association rules mining algorithm based on attribute reduction — ARTAR is put forward to deal with high dimensional data. The Attributes Reduction...
In this paper, we propose a novel post processing approach for on-line handwriting recognition. Differing from the existing linguistic knowledge-based methods, we make use of domain specific knowledge to improve the performance of recognition. Our system recognizes doctor's handwriting which often poses great challenges in readability, and then enhances the quality of recognized text by analyzing...
With large databases of document images available,a method for users to find keywords in documents will be useful. One approach is to perform Optical Character Recognition (OCR) on each document followed by indexing of the resulting text. However, if the quality of the document is poor or time is critical,complete OCR of all images is infeasible. This paper build upon previous works on Word Shape...
Perspective deformation is one of the main issues needed to be addressed in real-scene character recognition. An effective recognition approach, which is able to handle severe perspective deformation, is to employ cross ratio spectrum and dynamic time warping techniques. However, this solution suffers from a time complexity of O(n4). In this paper, a clustering based indexing method is proposed to...
There has been a large growth of online opinioned customer reviews in the recent years. Classifying such reviews into polarized ones would be beneficial in business intelligence and other application domains. This paper aims at finding a solution for the sentiment classification at a fine-grained level, namely the sentence level. The challenge is that because a sentiment expression is more free-style,...
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