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Titlebook: Computational Linguistics and Intelligent Text Processing; 12th International C Alexander Gelbukh Conference proceedings 2011 Springer Berl

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Democracy at the University of Chile,d form of these examples to the training set as new patterns. This cycle was continued until no new PTPs were detected. The process showed itself to be effective in requiring 5 cycles to create 371 true positives from 200 texts. We believe this gives 95% coverage of the TPs in the corpus.
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TEP: Tehran English-Persian Parallel Corpusd during data extraction and sentence alignment are addressed. To the best of our knowledge, TEP has been the first freely released large-scale (in order of million words) English-Persian parallel corpus.
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Comparing Manual Text Patterns and Machine Learning for Classification of E-Mails for Automatic Answrecision at 89 percent than the machine learning-based method that gave only 63 percent precision. The recall was slightly higher (66 percent) for the machine learning-based methods than for the text patterns (47 percent). We also found that 23 percent of the total e-mail flow was processed by the automatic e-mail answering system.
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Linda Shepard,George Rehrey,Dennis Grothins. We discuss how to interpret the topic chains to understand the news corpus by looking at long-term topics, temporary issues, and shifts of focus in the topic chains. We applied our framework to nine months of Korean Web news corpus and present our findings.
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