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When browsing news on the web, various emotions may be evoked in readers and furthermore cause different influence on their minds and life. We expect that emotional analysis and classification of text may provide good performance and significance to users surfing the Internet. Most previous research only focus on bi-emotion classification, that is, Positive and Negative, e.g., identifying whether...
In this paper we present a novel CAPTCHA that is based on the current hard AI problem of mixed-text (handwriting and printed-text) segmentation. The proposed CAPTCHA overlays generated handwritten word images on a generated printed-text background. We first propose a modification that allows for character level perturbations on an existing synthetic handwriting generation technique. These perturbations...
Authorship attribution is a growing field, moving from beginnings in linguistics to recent advances in text mining. Through this change came an increase in the capability of authorship attribution methods both in their accuracy and the ability to consider more difficult problems. Research into authorship attribution in the 19th century considered it difficult to determine the authorship of a document...
Classification and clustering are frequently-used methods in data excavation technology. This paper introduces the idea of text clustering into the categorization algorithm study. The authors also attempt to use the text categorization pattern of self'-initiated learning to design a clustering-based text categorization algorithm, in the purpose of reducing the dimension of training set and raising...
Chinese segmentation is an important issue in Chinese text processing. The traditional segmentation methods those depend on an existing dictionary suffer the drawbacks when encounter unknown words. The paper proposed a segmenting algorithm for Chinese based on extracting local context information. It added the context information of the testing text into the local PPM statistical model so as to guide...
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