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Employing the centering theory in pronoun resolution from the semantic perspective

Employing the centering theory in pronoun resolution from th...

2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Kong, Fang Zhou, Guo Dong Zhu, Qiaoming JiangSu Provincial Key Lab. for Computer Information Processing Technology School of Computer Science and Technology Soochow University Suzhou 215006 China

In this paper, we employ the centering theory in pronoun resolution from the semantic perspective. First, diverse semantic role features with regard to different predicates in a sentence are explored. Moreover, given a pronominal anaphor, its relative ranking among all the pronouns in a sentence, according to relevant semantic role information and its surface position, is incorporated. In particular, the use of both the semantic role features and the relative pronominal ranking feature in pronoun resolution is guided by extending the centering theory from the grammatical level to the semantic level in tracking the local discourse focus. Finally, detailed pronominal subcategory features are incorporated to enhance the discriminative power of both the semantic role features and the relative pronominal ranking feature. Experimental results on the ACE 2003 corpus show that the centering-motivated features contribute much to pronoun resolution. © 2009 ACL and AFNLP.

关键词： Semantics

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Homeomorphism Prior for False Positive and Negative Problem in Medical Image Dense Contrastive Representation Learning

arXiv

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arXiv 2025年

作者： He, Yuting Wang, Boyu Ge, Rongjun Chen, Yang Yang, Guanyu Li, Shuo Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Nanjing China Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Nanjing China School of Instrument Science and Engineering Southeast University Nanjing China Department of Computer Science Western University LondonONN6A 3K7 Canada Department of Biomedical Engineering Department of Computer and Data Science Case Western Reserve University ClevelandOH44106 United States

Dense contrastive representation learning (DCRL) has greatly improved the learning efficiency for image dense prediction tasks, showing its great potential to reduce the large costs of medical image collection and dense annotation. However, the properties of medical images make unreliable correspondence discovery, bringing an open problem of large-scale false positive and negative (FP&N) pairs in DCRL. In this paper, we propose GEoMetric vIsual deNse sImilarity (GEMINI) learning which embeds the homeomorphism prior to DCRL and enables a reliable correspondence discovery for effective dense contrast. We proposes a deformable homeomorphism learning (DHL) which models the homeomorphism of medical images and learns to estimate a deformable mapping to predict the pixels’ correspondence under the condition of topological preservation. It effectively reduces the searching space of pairing and drives an implicit and soft learning of negative pairs via gradient. We also proposes a geometric semantic similarity (GSS) which extracts semantic information in features to measure the alignment degree for the correspondence learning. It will promote the learning efficiency and performance of deformation, constructing positive pairs reliably. We implement two practical variants on two typical representation learning tasks in our experiments. Our promising results on seven datasets which outperform the existing methods show our great superiority. We will release our code at a companion website. Copyright © 2025, The Authors. All rights reserved.

关键词： Contrastive Learning

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Towards termination criteria of ant colony optimization

Towards termination criteria of ant colony optimization

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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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Dependency-driven feature-based learning for extracting protein-protein interactions from biomedical text

Dependency-driven feature-based learning for extracting prot...

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23rd International Conference on Computational Linguistics, Coling 2010

作者： Liu, Bing Qian, Longhua Wang, Hongling Zhou, Guodong Jiangsu Provincial Key Lab for Computer Information Processing Technology School of Computer Science and Technology Soochow University China

Recent kernel-based PPI extraction systems achieve promising performance because of their capability to capture structural syntactic information, but at the expense of computational complexity. This paper incorporates dependency information as well as other lexical and syntactic knowledge in a feature-based framework. Our motivation is that, considering the large amount of biomedical literature being archived daily, feature-based methods with comparable performance are more suitable for practical applications. Additionally, we explore the difference of lexical characteristics between biomedical and newswire domains. Experimental evaluation on the AIMed corpus shows that our system achieves comparable performance of 54.7 in F1-Score with other state-of-the-art PPI extraction systems, yet the best performance among all the feature-based ones.

关键词： Syntactics

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Dependency-driven anaphoricity determination for coreference resolution

Dependency-driven anaphoricity determination for coreference...

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23rd International Conference on Computational Linguistics, Coling 2010

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

This paper proposes a dependency-driven scheme to dynamically determine the syntactic parse tree structure for tree kernel- based anaphoricity determination in coreference resolution. Given a full syntactic parse tree, it keeps the nodes and the paths related with current mention based on constituent dependencies from both syntactic and semantic perspectives, while removing the noisy information, eventually leading to a dependency-driven dynamic syntactic parse tree (D-DSPT). Evaluation on the ACE 2003 corpus shows that the D-DSPT outperforms all previous parse tree structures on anaphoricity determination, and that applying our anaphoricity determination module in coreference resolution achieves the so far best performance.

关键词： Syntactics

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Research of event pronoun resolution

Research of event pronoun resolution

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2011 International Conference on Asian Language processing, IALP 2011

作者： Zhang, Ning Kong, Fang Li, Peifeng 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

Event anaphora resolution plays an important role in discourse analysis. In comparison with general noun phrases, pronouns carry little information of themselves, resolving the event pronouns is a more difficult task. This paper proposes a machine learning-based framework for event pronoun resolution. All kinds of features, including both flat and structural features, are explored for event pronoun resolution. Experiments on OntoNotes corpus show that both flat and structural features are very effective for this task. © 2011 IEEE.

关键词： Learning systems

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Exploiting constituent dependencies for tree kernel-based semantic relation extraction

Exploiting constituent dependencies for tree kernel-based se...

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22nd International Conference on Computational Linguistics, Coling 2008

作者： Qian, Longhua Zhou, Guodong Kong, Fang Zhu, Qiaoming Qian, Peide Jiangsu Provincial Key Lab. for Computer Information Processing Technology School of Computer Science and Technology Soochow University 1 Shizi Street Suzhou 215006 China

ISBN: (纸本)9781905593446

This paper proposes a new approach to dynamically determine the tree span for tree kernel-based semantic relation extraction. It exploits constituent dependencies to keep the nodes and their head children along the path connecting the two entities, while removing the noisy information from the syntactic parse tree, eventually leading to a dynamic syntactic parse tree. This paper also explores entity features and their combined features in a unified parse and semantic tree, which integrates both structured syntactic parse information and entity-related semantic information. Evaluation on the ACE RDC 2004 corpus shows that our dynamic syntactic parse tree outperforms all previous tree spans, and the composite kernel combining this tree kernel with a linear state-of-the-art feature-based kernel, achieves the so far best performance. © 2008. Licensed under the Creative Commons.

关键词： Semantics

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Research on cross-document coreference of Chinese person name

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

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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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Wireless Service Prediction Algorithm in Mobile Social Environment 2

Wireless Service Prediction Algorithm in Mobile Social Envir...

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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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