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中文摘要：
关联检测是话题检测与跟踪领域的基础性研究，其任务是检测任意新闻报道对是否论述同一话题．通过分析报道内容的结构关系和语义的分布规律，提出基于语义域语言模型的关联性检测方法，并在此基础上检验融入依存分析的语义描述策略对该模型性能的影响．实验采用TDT4中文语料进行评测，结果显示语义域语言模型显著改进了现有检测系统的性能，其最小DET代价降低了约3个百分点．
英文摘要：
Topic link detection is a foundational research in the field of topic detection and tracking, which detects whether two random stories talk about the same topic. This paper proposes a method of applying semantic domain language model to link detection, based on the structure relation among contents and the semantic distribution in a story, and also verifies the influence of the strategy incorporating dependency parsing into semantic description. Evaluation on Chinese Corpus of TDT4 show that the semantic domain language model substantially improved the performance of current detection system, whose minimum DET cost is reduced by about 3 percent.
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A new query expansion approach using collocation relationships in language models for information re
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