Hongying Zan

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The Robust Retrieval track is a traditional ad hoc retrieval task with the focus on individual topic effectiveness. This track provides us an opportunity to do experiments on our recently proposed IR model using a word-by-sense matrix document representation, which was called Sense Matrix Model (SMM) [Swen 2003, 2004]. For the first time to extensively test(More)
Selectional preference (SP) is an important semantic knowledge. It can be used in various natural language processing tasks, including metaphor computing, lexicon building, syntactic structure disambiguation, word sense disambiguation, semantic role labeling, etc. However, handcrafted SP knowledge can not meet the requirement of large scale real text(More)
Selectional preference (SP) is an important kind of semantic knowledge. It can be used in various natural language processing tasks, including metaphor computing, lexicon building, syntactic structure disambiguation, word sense disambiguation, semantic role labeling, anaphora resolution, etc. This paper presents and compares two computational models for(More)
A self-adaptive parameter selection algorithm for parameter q in one-dimensional Tsallis entropy image thresholding is presented based on optimization algorithm. The method can get the suitable parameter and the optimal threshold value for different kinds of images, which selects the parameter based on the uniformity measure, an image segmentation quality(More)
We have a “Trinity” way for the recognition of Chinese modality “LE”, in which dictionary, usage rule base and usage corpora combine as the knowledge base. Handcrafted rules can hardly cover all usages in the real texts. So this paper proposes an error driven method for the automatic rules improvement. Experimental results show(More)