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26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012

作者： Yang, Shaohua Zhao, Hai Lu, Bao-Liang MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9789791421171

This paper introduces a new approach to solve the Chinese Pinyin-to-character (PTC) conversion problem. The conversion from Chinese Pinyin to Chinese character can be regarded as a transformation between two different languages (from the Latin writing system of Chinese Pinyin to the character form of Chinese,Hanzi), which can be naturally solved by machine translation framework. PTC problem is usually regarded as a sequence labeling problem, however, it is more difficult than any other general sequence labeling problems, since it requires a large label set of all Chinese characters for the labeling task. The essential difficulty of the task lies in the high degree of ambiguities of Chinese characters corresponding to Pinyins. Our approach is novel in that it effectively combines the features of continuous source sequence and target sequence. The experimental results show that the proposed approach is much faster, besides, we got a better result and outperformed the existing sequence labeling approaches. © 2012 The PACLIC.

关键词： machine translation

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Hybrid rule-based algorithm for coreference resolution

Hybrid rule-based algorithm for coreference resolution

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2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, EMNLP-CoNLL 2012 - Shared Task: Modeling Multilingual Unrestricted Coreference in OntoNotes

作者： Shou, Heming Zhao, Hai Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781937284459

This paper describes our coreference resolution system for the CoNLL-2012 shared task. Our system is based on the Stanford's dcoref deterministic system which applies multiple sieves with the order from high precision to low precision to generate coreference chains. We introduce the newly added constraints and sieves and discuss the improvement on the original system. We evaluate the system using OntoNotes data set and report our results of average F-score 58.25 in the closed track. © 2012 Association for Computational Linguistics.

关键词： Sieves

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Chinese coreference resolution via ordered filtering

Chinese coreference resolution via ordered filtering

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作者： Zhang, Xiaotian Wu, Chunyang Zhao, Hai Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University China

ISBN: (纸本)9781937284459

We in this paper present the model for our participation (BCMI) in the CoNLL-2012 Shared Task. This paper describes a pure rule-based method, which assembles different filters in a proper order. Different filters handle different situations and the filtering strategies are designed manually. These filters are assigned to different ordered tiers from general to special cases. We participated in the Chinese and English closed tracks, scored 51.83 and 59.24 respectively. © 2012 Association for Computational Linguistics.

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Differently implicational α-universal triple I restriction method of (1, 2, 2) type

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Journal of Systems Engineering and Electronics 2012年第4期23卷 560-573页

作者： Yiming Tang Fuji Ren Yanxiang Chen Information and Communication Engineering Postdoctoral Research Station Hefei University of TechnologyHefei 230009P.R.China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191P.R.China Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of TechnologyHefei 230009P.R.China Institute of Technology and Science The University of TokushimaMinami Josanjima770-8506Japan

From the viewpoints of both fuzzy system and fuzzy reasoning, a new fuzzy reasoning method which contains the α- triple I restriction method as its particular case is proposed. The previous α-triple I restriction principles are improved, and then the optimal restriction solutions of this new method are achieved, especially for seven familiar implications. As its special case, the corresponding results of α-triple I restriction method are obtained and improved. Lastly, it is found by examples that this new method is more reasonable than the α-triple I restriction method.

关键词： fuzzy reasoning fuzzy system triple I method triple Irestriction method compositional rule of inference method.

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Adaptive facial expression recognition based on a weighted component and global features

Adaptive facial expression recognition based on a weighted c...

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4th International Conference on Digital Home, ICDH 2012

作者： Li, Rui Hu, Min Wang, XiaoHua Xu, Liangfeng Huang, Zhong Chen, Xing AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Hefei China School of Computer and Information Hefei University of Technology Hefei China

ISBN: (纸本)9781467313483

An adaptive facial expression recognition method based on component and global features is presented in this paper. The facial component features are highlighted for purpose of improving facial expression percent correct rate. Firstly, eyebrows, eyes, nose and mouth are divided from a facial expression image and then the component features would be gotten from these organ images which are processed by Gabor wavelets. The weighted adaptive algorithm would be used to calculate the component feature weights, the weighted component features fuse with the global feature to get a feature fusion matrix. Finally, Weighted Principal Component Analysis (WPCA) and Fisher Linear Discriminant (FLD) methods are used to reduce dimensions and classify facial expression. Experimental results show that the algorithm proposed in this paper has much more accurate recognition rate compared with the global Gabor wavelets, PCA and FLD integrated algorithm. © 2012 IEEE.

关键词： Adaptive algorithms

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Automated quality assessment of web pages from textual content

Automated quality assessment of web pages from textual conte...

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2012 International Conference on machine Learning and Cybernetics, ICMLC 2012

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China

ISBN: (纸本)9781467314855

Given the vastness of Internet, search engines have to find not only relevant but also high-quality web pages to satisfy users' information need. At present, most quality assessing methods for web pages are based on link analysis and user feedbacks. Considering that users acquire information from web pages mainly through reading their text, this paper addresses automated quality assessment of web pages from textual content. This paper surveys related works on assessing text's quality, summarizes quality-related features, and examines them with a real-word data set. Experimental results show that features based on the length of text are the most effective, while combining length features with other features such as part-of-speech tags and readability can further improve the accuracy. © 2012 IEEE.

关键词： Websites

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PPLSA: Parallel probabilistic latent semantic analysis based on MapReduce

PPLSA: Parallel probabilistic latent semantic analysis based...

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7th IFIP International Conference on Intelligent Information Processing, IIP 2012

作者： Li, Ning Zhuang, Fuzhen He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University Chinese Academy of Sciences Beijing China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding China

ISBN: (纸本)9783642328909

PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalability of computation in PLSA. In this paper, we propose a parallel PLSA algorithm called PPLSA to accommodate large corpus collections in the MapReduce framework. Our solution efficiently distributes computation and is relatively simple to implement. © 2012 IFIP International Federation for Information Processing.

关键词： MapReduce

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A MMSM-based Hybrid Method for Chinese MicroBlog Word Segmentation 2

A MMSM-based Hybrid Method for Chinese MicroBlog Word Segmen...

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2nd CIPS-SIGHAN Joint Conference on Chinese Language Processing, CLP 2012

作者： Sun, Xiao Li, Chengcheng Tang, Chenyi Ye, Jiaqi AnHui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and Information Hefei University of Technology Anhui Hefei230009 China School of Computer Science and Engineering Dalian University of Technology Liaoning Dalian116023 China

After years of researches, Chinese word segmentation has achieved quite high precisions for formal style text. However, the performance of segmentation is not so satisfying for MicroBlog corpora. In this paper we describe a scheme for Chinese word segmentation for, MicroBlog which integrates the character-based and word-based information in the directed graph generated by MMSM model. Word-level information is effective for analysis of known words, while character-level information is useful for analysis of unknown words. A multi-chain unequal states CRF model is proposed. The proposed multi-chain unequal states CRF has two state chains with unequal states which can recognize the POS tag simultaneously. The hybrid model was effective and adopted in real-world system. © 2021 CLP 2012 - 2nd CIPS-SIGHAN Joint Conference on Chinese Language Processing. All Rights Reserved.

关键词： Directed graphs

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EEG-based emotion recognition in listening music by using support vector machine and linear dynamic system

EEG-based emotion recognition in listening music by using su...

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19th International Conference on Neural Information Processing, ICONIP 2012

作者： Duan, Ruo-Nan Wang, Xiao-Wei Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China MOE Key Laboratory of Systems Biomedicine Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200240 China

ISBN: (纸本)9783642344770

This paper focuses on the variation of EEG at different emotional states. We use pure music segments as stimuli to evoke the exciting or relaxing emotions of subjects. EEG power spectrum is adopted to form features, power spectrum, differential asymmetry, and rational asymmetry. A linear dynamic system approach is applied to smooth the feature sequence. Minimal-redundancy-maximal-relevance algorithm and principal component analysis are used to reduce the dimension of features. We evaluate the performance of support vector machine, k-nearest neighbor classifiers and least-squares classifiers. The accuracy of our proposed method reaches 81.03% on average. And we show that the frequency bands, beta and theta, perform better than other frequency bands in the task of emotion recognition. © 2012 Springer-Verlag.

关键词： Emotion Recognition

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Parallel implementation of apriori algorithm based on MapReduce

Parallel implementation of apriori algorithm based on MapRed...

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13th ACIS International Conference on Software Engineering, Artificial intelligence, Networking, and Parallel/Distributed computing, SNPD 2012

作者： Li, Ning Zeng, Li He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100139 China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

ISBN: (纸本)9780769547619

Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorithms that can handle large volumes of data becomes a challenging task due to the large databases. In this paper, we implement a parallel Apriori algorithm based on MapReduce, which is a framework for processing huge datasets on certain kinds of distributable problems using a large number of computers (nodes). The experimental results demonstrate that the proposed algorithm can scale well and efficiently process large datasets on commodity hardware. © 2012 IEEE.

关键词： MapReduce

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