...搜索 一词多义 词义聚类 [gap=704]Key words】：Internet; synonym; information retrieval; polysemy; semantic clustering ...
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To solve automatic predicate-verb choosing for argument, this paper gives semantics preference method based on Minumum Description Length(MDL) and Latent Semantic Clustering(LSC). MDL is used to calculate of each verb-noun pair.
为实现谓语动词对论元的自动选择，提出基于最小描述长度(MDL)和潜在语义聚类(LSC)的语义优选方法。
参考来源 - 基于MDL和LSC的语义优选方法·2,447,543篇论文数据，部分数据来源于NoteExpress
Combined with semantic similarity of text data, this paper gives a method of text data clustering based on semantic density.
结合文本数据的语义相似度，给出一种基于语义密度文本数据聚类的方法。
Since the semantic sequence is only related to text, it is available for incremental clustering.
由于所提算法的语义序列只与文本自身相关，所以它适用于增量式聚类。
This paper presents a new method of text clustering by using the latent semantic index (LSI) and self-organizing neural network (SNN).
根据隐含语义索引（LSI）理论和动态自组织映射神经网络理论，提出了一种文本聚类的新方法。
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