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Research on cross-document coreference of Chinese person name

Research on cross-document coreference of Chinese person nam...

引用

2011 International Conference on Asian Language processing, IALP 2011

作者： Ni, Ji Kong, Fang Li, Peifeng Zhu, Qiaoming JiangSu Provincial Key Lab. for Computer Information Processing Technology Soochow University Suzhou China School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9780769545547

In reality, different persons often have the same person name. The Person Cross Document Co-reference Resolution is a task, which requires that all and only the textual mentions of an entity of type Person be individuated in a collection of text documents. In this paper, we implement a Chinese Person Name Cross Document Co-reference Resolution System. First, we utilize name identification module to recognize all person names of the texts, and then classify the document collection of same person name by rules preliminarily, and at last, we compute similarities of each classification based on VSM, according to the prior similarities, the system get the final classification results. We test the system on 30 usual Chinese names of the corpus provided by CLP, and average F measure is 85.9%. © 2011 IEEE.

关键词： information retrieval systems

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Research of noun phrase coreference resolution

Research of noun phrase coreference resolution

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2011 International Conference on Asian Language processing, IALP 2011

作者： Gao, Junwei Kong, Fang Li, Peifeng Zhu, Qiaoming JiangSu Provincial Key Lab. for Computer Information Processing Technology Soochow University Suzhou China School of Computer Science and Technology Soochow University Suzhou China

ISBN: (纸本)9780769545547

Coreference resolution is an important subtask in natural language processing systems. The process of it is to find whether two expressions in natural language refer to the same entity in the world. Machine learning approaches to this problem have been reasonably successful, operating primarily by recasting the problem as a classification task. A great deal of research has been done on this task in English, using approaches ranging from those based on linguistics to those based on machine learning. In Chinese, however, much less work has been done in this area. The lack of public resources is a big problem in the research of Chinese NLP. The other problem is that some features are more difficult to get than those features of English. In this paper, We present a noun phrase coreference system that refers to the work of Soon et al. (2001). We also explore the impact of various features on our system's performance. Experiments on the Chinese portion of OntoNotes 3.0 show that the platform achieves a good performance. © 2011 IEEE.

关键词： Natural language processing systems

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Towards termination criteria of ant colony optimization

Towards termination criteria of ant colony optimization

引用

3rd International Conference on Natural Computation, ICNC 2007

作者： Lv, Qiang Xia, Oyan School of Computer Science and Technology Suzhou University Suzhou Jiangsu 215006 China Provincial Key Lab. for Computer Information Processing Technology Suzhou Jiangsu 215006 China

ISBN: (纸本)0769528759

Ant colony optimization (ACO for short) has been proved a successful meta-heuristic by a huge of empirical studies. This paper discusses the termination criteria of ACO and therefore provides research ideas to other meta-heuristics. A general discussion about four types of termination criteria has been firstly discussed in this article. Then some measures of convergence based on pheromone have been introduced. And a new termination criterion based on Bayesian approach is presented. Finally a new convergence proof for a class of ACO algorithms is presented. © 2007 IEEE.

关键词： Heuristic methods

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Wireless Service Prediction Algorithm in Mobile Social Environment 2

Wireless Service Prediction Algorithm in Mobile Social Envir...

引用

2017 IEEE 2nd International Conference on Big Data Analysis（ICBDA 2017）

作者： Hui Zhang Min Wang Jiangsu Key Lab of Wireless Communications Nanjing University of Posts and Telecommunications Provincial Key Laboratory for Computer Information Processing Technology Soochow University

ISBN: (纸本)9781509036202

First,according to characteristics of mobile social environment,by using optimization models based on similarity degree and interaction degree respectively,the optimal correlated users can be selected for analyzing two main factors of a target user's behaviors(***-term habits and shortterm influences);furthermore,an adaptive update strategy based on fuzzy theory is proposed to describe the importance of two factors in real time and quantitative ***,an improved Apriori theory is introduced to predict user service behaviors accurately;particularly,a new update mechanism for Apriori sample database is built to effectively integrate the samples of optimal correlated ***,simulation results verify the effectiveness of proposed algorithm.

关键词： mobile social environment user behavior prediction fuzzy theory adaptive update strategy improved Apriori theory

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Classification rules mining based on SOFM networks

Classification rules mining based on SOFM networks

引用

MIPPR 2005: Geospatial information, Data Mining, and Applications

作者： Yao, Min Jiang, Zhiwei Shen, Bin College of Computer Zhejiang University Hangzhou 310027 China Provincial Key Lab. for Computer Information Processing Technology in Jiangsu Suzhou University Suzhou 215006 China

Self-organization feature mapping (SOFM) networks have strong ability for self-learning and self-adaptive. According to the characteristics of human thought, this paper constructed a kind of combined criterion, which may be used to guide the learning of self-organization feature mapping network. Then this paper presents subsection algorithm, amalgamation algorithm and dynamical adaptive algorithm for SOFM networks so as to solve a kind of problems of classification rule mining. Finally, a practical example shows its flexibility and practicability.

关键词： Self organizing maps

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An unsupervised discriminative random vector functional link network for efficient data clustering 4

An unsupervised discriminative random vector functional link...

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4th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2021

作者： Zhang, Yikai Zhu, Qi Peng, Yong Kong, Wanzeng School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Provincial Key Lab. for Computer Information Processing Technology Soochow University Suzhou215123 China

ISBN: (纸本)9781665413220

Random Vector Functional Link (RVFL) is a single hidden layer feed forward network which can be trained with non-iterative learning methods. Concretely, the input weights and hidden biases in RVFL can be randomly generated and then the calculation of the output weights can be reduced to solve a regularized least squares regression formula. Though RVFL network obtained promising performance in diverse applications, most of its current variants work mainly for supervised tasks such as classification and regression while less effort was made to utilize the unlab.led data. In this paper, we propose an unsupervised RVFL model by simultaneously considering the local manifold structure and the global discriminative information of data. The newly formulated unsupervised discriminative RVFL (UDRVFL) model can be efficiently solved by handling an eigen-value decomposition operation. We conduct experiments by comparing UDRVFL with several state-of-the-arts on representative benchmark data sets and the results demonstrate that it has very competitive performance in data clustering. © 2021 IEEE.

关键词： Iterative methods

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Dependency tree-based anaphoricity determination for coreference resolution

Dependency tree-based anaphoricity determination for corefer...

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International Conference on Asian Language processing

作者： Kong, Fang Zhou, Jianmei Zhou, Guodong Zhu, Qiaoming JiangSu Provincial Key Lab. for Computer Information Processing Technology China School of Computer Science and Technology Soochow University Suzhou China Computer Science and Technology School NanTong University NanTong China

ISBN: (纸本)9780769542881

This paper proposes a new scheme to determine the tree span structure for tree kernel-based anaphoricity determination in coreference resolution. Given a sentence and current mention, it gets all the dependencies, encodes the order of all the words, constructs the corresponding dependency tree and keeps the nodes and the paths related with current mention based on constituent dependencies, while removing the noisy information, eventually leading to a dynamical dependency tree (DDT). Evaluation on the ACE 2003 corpus shows that the DDT is effective for anaphoricity determination, and that applying our anaphoricity determination module in coreference resolution achieves the improvement of performance. © 2010 IEEE.

关键词： Anaphoricity determination Coreference resolution Dependency tree Coreference Resolution DDT DEPENDENCE

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Dependency tree-based SRL with proper pruning and extensive feature engineering

Dependency tree-based SRL with proper pruning and extensive ...

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12th Conference on Computational Natural Language Learning, CoNLL 2008

作者： Wang, Hongling Wang, Honglin Zhou, Guodong Zhu, Qiaoming Jiang Su Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow University Suzhou 215006 China

ISBN: (纸本)1905593481

This paper proposes a dependency tree-based SRL system with proper pruning and extensive feature engineering. Official evaluation on the CoNLL 2008 shared task shows that our system achieves 76.19 in lab.led macro F1 for the overall task, 84.56 in lab.led attachment score for syntactic dependencies, and 67.12 in lab.led F1 for semantic dependencies on combined test set, using the standalone MaltParser. Besides, this paper also presents our unofficial system by 1) applying a new effective pruning algorithm;2) including additional features;and 3) adopting a better dependency parser, MSTParser. Unofficial evaluation on the shared task shows that our system achieves 82.53 in lab.led macro F1, 86.39 in lab.led attachment score, and 78.64 in lab.led F1, using MSTParser on combined test set. This suggests that proper pruning and extensive feature engineering contributes much in dependency tree-based SRL. © 2008.

关键词： Semantics

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Context-Sensitive Convolution Tree Kernel for Pronoun Resolution 3

Context-Sensitive Convolution Tree Kernel for Pronoun Resolu...

引用

3rd International Joint Conference on Natural Language processing, IJCNLP 2008

作者： Zhou, GuoDong Kong, Fang Zhu, Qiaoming JiangSu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow Univ. Suzhou215006 China

This paper proposes a context-sensitive convolution tree kernel for pronoun resolution. It resolves two critical problems in previous researches in two ways. First, given a parse tree and a pair of an anaphor and an antecedent candidate, it implements a dynamic-expansion scheme to automatically determine a proper tree span for pronoun resolution by taking predicate- and antecedent competitor-related information into consideration. Second, it applies a context-sensitive convolution tree kernel, which enumerates both context-free and context-sensitive sub-trees by considering their ancestor node paths as their contexts. Evaluation on the ACE 2003 corpus shows that our dynamic-expansion tree span scheme can well cover necessary structured information in the parse tree for pronoun resolution and the context- sensitive tree kernel much outperforms previous tree kernels. © 2008 IJCNLP 2008 - 3rd International Joint Conference on Natural Language processing, Proceedings of the Conference. All rights reserved.

关键词： Convolution

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Semi-Supervised Learning for Relation Extraction 3

Semi-Supervised Learning for Relation Extraction

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3rd International Joint Conference on Natural Language processing, IJCNLP 2008

作者： Zhou, Guo Dong Li, Jun Hui Qian, Long Hua Zhu, Qiaoming Jiangsu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow Univ. Suzhou215006 China

This paper proposes a semi-supervised learning method for relation extraction. Given a small amount of lab.led data and a large amount of unlab.led data, it first bootstraps a moderate number of weighted support vectors via SVM through a co-training procedure with random feature projection and then applies a lab.l propagation (LP) algorithm via the bootstrapped support vectors. Evaluation on the ACE RDC 2003 corpus shows that our method outperforms the normal LP algorithm via all the availab.e lab.led data without SVM bootstrapping. Moreover, our method can largely reduce the computational burden. This suggests that our proposed method can integrate the advantages of both SVM bootstrapping and lab.l propagation.s. © 2008 IJCNLP 2008 - 3rd International Joint Conference on Natural Language processing, Proceedings of the Conference. All rights reserved.

关键词： Extraction

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