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检索条件"任意字段=2003 International Conference on Natural Language Processing and Knowledge Engineering"

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MACHINE LEARNING FOR COLLOCATION IDENTIFICATION

MACHINE LEARNING FOR COLLOCATION IDENTIFICATION

引用

2003 international conference on natural language processing and knowledge engineering

作者： Shouxun YANG Foreign Language Teaching and Research Press Beijing Foreign Studies University 19 North Xisanhuan Avenue

ISBN: (纸本)0780379020

Previous works on automatic identification or extraction of collocations from large scale corpora generally make use of certain statistical measures to test for significance of association to yield n-best collocation candidates for human scrutiny,optionally with linguistic preprocessing and linguistic *** drawback of these approaches is we can only take advantage of one single statistical test(optionally in association with simple frequency threshold),even though we often calculate the values of several statistical *** exploring a scheme to combine two or more different tests is out of the *** paper reports experiments with machine learning for collocation identification using a variety of statistical association measurements. In particular,we develop a new decision tree learning algorithm based on C4.5 to be used for learning tasks with unbalanced *** experiment results are presented and briefly discussed.

关键词： Decision tree learning Collocation identification Association measures

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CHINESE PARTIAL PARSER FOR AUTOMATIC EXTRACTION OF VERB GRAMMATICAL COLLOCATIONS

CHINESE PARTIAL PARSER FOR AUTOMATIC EXTRACTION OF VERB GRAM...

引用

2003 international conference on natural language processing and knowledge engineering

作者： Yuqi Zhang Qiang Zhou State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University

ISBN: (纸本)0780379020

Grammatical Collocation is one of the important lexical knowledge for NLP and getting it automatically is useful for many *** this paper we present a parser based on phrases to extract grammatical collocations of Chinese *** the instruction of collocation templates,the parser combine base phrases to common phrases,and to grammatical collocation chunks with a chart-parsing *** the algorithm,we apply a new process sequence referring to the special task,which starts from each verb,then processes to the left and right. In this ways,we are able to achieve precision of 61.4%,55.4%,and 54.8%for science,news and novel corpus respectively.

关键词： Grammatical collocation Verb Partial parser

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COMPARATIVE EXPERIMENTS ON TASK CLASSIFICATION FOR SPOKEN language UNDERSTANDING USING NAVE BAYES CLASSIFIER

COMPARATIVE EXPERIMENTS ON TASK CLASSIFICATION FOR SPOKEN LA...

引用

2003 international conference on natural language processing and knowledge engineering

作者： Weilin Wu Ruzhan Lu Zheng Liu Department of Computer Science and Engineering Shanghai Jiao Tong University

ISBN: (纸本)0780379020

This paper presents a series of comparative experiments on using statistical classifiers for task *** experiments focus on three aspects: the effect of different features on the performance of the classifier,the robustness of classifiers with different features on data variability and the effect of size of training data on the performance of the *** Chinese input sentences,three linguistics units can be used as the features:Chinese characters,Chinese words and semantic constituents. Both advantages and disadvantages of them are analyzed in details.A controlled study using Naive Bayes classifiers is conducted to examine the impact of different features on the performance of classifiers. The classifiers with different features are evaluated respectively on the clean and noisy test data to investigate their *** curves of the classifiers with different features are given to show the effect of size of training data.

关键词： Task Classification Naive Bayes Classifier Comparative Study

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GREETINGS FROM THE PROGRAM COMMITTEE

GREETINGS FROM THE PROGRAM COMMITTEE

引用

2003 international conference on natural language processing and knowledge engineering

作者： Y.X.ZHONG IEEE NLP-KE 2003 PC Chair Beijing University of Posts and Telecommunications

＜正＞Respectable Colleagues and Dear Friends, On behalf of the Program Committee,2003 Beijing international conference on natural language processing and knowledge engineering,NLP-KE’03-Beijing,I would like to extend to you our warmest welcome and most cordial greetings. The theme of natural language processing and Understanding has become one of the focuses in AI research and the related fields due to the great needs and challenges from the worldwide trend of *** explains why the researchers over the world feel a high responsibility on their shoulders and why so many colleagues and friends would like to join in

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language processing for name and address reading in Hungarian

Language processing for name and address reading in Hungaria...

引用

IEEE international conference on natural language processing and knowledge engineering (NLP-KE)

作者： G. Nemeth C. Zainko G. Kiss M. Fek G. Gordos Olaszy G Department of Telecommunications & Media Informatics Budapest University of Technology and Economics Budapest Hungary Kernpelen Farkas Speech Research Laboratory Linguistics Institute of Hungarian Academy of Sciences Hungary

Name and address reading is an important combined application area of language processing and text-to-speech (TTS) systems. It is the cornerstone of both traditional reverse directory telephone services and new, location based, traffic and tour guide applications. The language processing aspects of a solution for Hungarian is described. The work was based on the analysis of a subscriber database containing about 3 million records (there are about 10 million Hungarian citizens). Categories of name and address elements were defined. A program for the automatic classification of database records was developed. Statistical parameters were derived about proper/legal names and addresses. Based on these results text corpora for enriching the TTS acoustic database were designed. Reading strategies and related special algorithms and tables were developed for the description of complex name categories. Our results may be applied for similar tasks of other languages with comparable linguistic and statistical features.

关键词： Speech synthesis Databases natural languages GSM Informatics Telephony Continuous improvement Acoustic applications Humans Laboratories

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SEMANTIC INFERENCE BASED ON ONTOLOGY FOR MEDICAL FAQ MINING

SEMANTIC INFERENCE BASED ON ONTOLOGY FOR MEDICAL FAQ MINING

引用

2003 international conference on natural language processing and knowledge engineering

作者： Jui-Feng Yeh Ming-Jun Chen Chung-Hsien Wu Department of Computer Science and Information Engineering National Cheng Kung University

ISBN: (纸本)0780379020

＜正＞This paper presents an approach to semantic inference for FAQ mining based on *** questions are classified into ten intension categories using predefined question stemming *** answers in the FAQ database are also clustered using latent semantic analysis（LSA） and K-means *** FAQ mining,given a query,the question part and answer part in an FAQ questionanswer pair is matched with the input query, ***,the probabilities estimated from these two parts are integrated and used to choose the most likely answer for the input *** approaches are experimented on a medical FAQ *** results show that the proposed approach achieved a retrieval rate of 90%and outperformed the keyword-based approach.

关键词： FAQ question stemming latent semantic analysis Ontology Semantic Inference

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LEARNING FACE MARKS FOR natural language DIALOGUE SYSTEMS

LEARNING FACE MARKS FOR NATURAL LANGUAGE DIALOGUE SYSTEMS

引用

2003 international conference on natural language processing and knowledge engineering

作者： Junpei NAKAMURA Takeshi IKEDA Nobuo INUI Yoshiyuki KOTANI Department of Computer Information and Communication SciencesTokyo University of Agriculture and Technology 2-24-16 Nakacho Koganei Tokyo184-8588Japan

Face marks figures of faces which consist of characters such as(^^),and are effective for expressing emotions in a text-dialogue *** usually determine face marks from history of emotional elements and actional *** paper proposes a method of learning face marks for a natural language dialogue system from chat dialogue data in the Internet,*** use a back propagation error learning of a three-layer neural network to learn a model of face *** this neural network,the input neurons express emotional parameters and actional categories of texts,and the output neurons express parts of face marks:mouth,eyes,arms,and optional *** experimental results showed that the learning error was 0.19,and we could get the performance approximately 93%permissible value for the learning set of dialogues and approximately 60 %for the evaluation set of *** also showed that our system acquired the good information of relationship between parts of face marks and emotional and actional elements.

关键词： Face marks Emotion model Dialogue Act Neural network

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AUTOMATIC EXTRACTION OF THE UNLISTED TERMS IN THE FIELD OF INFORMATION TECHNOLOGY BASED ON THE DYNAMIC CIRCULATION CORPUS

AUTOMATIC EXTRACTION OF THE UNLISTED TERMS IN THE FIELD OF I...

引用

2003 international conference on natural language processing and knowledge engineering

作者： Qiangjun WANG Isabella Park Pu ZHANG College of Humanity Hebei Unversity 88 Hezuo RoadBaodingHebei071002China Woosong University 17-2 Jayang-dongDong-kuDaejeon.300-718Korea Beijing Language and Culture University 15 Xuyuan RoadBeijing100083China

ISBN: (纸本)0780379020

This paper discusses automatic extraction of the unlisted terms in the field of Information Technology based on the large-scale DCC(Dynamic Circulation Corpus),under the theory of Dynamic Updating of language and *** proposes the concept of Concatenation Index to decide whether a character string is a word/phrase or *** also presents a new approach named "Concatenation Index + TFIDF" for extracting unlisted terms in large scale corpus of a certain *** experiment selects the texts,around 17 million Chinese characters,in the field of IT (Information Technology) as the object corpus;and the texts,around 600 million Chinese characters,in the field of common usage as the contrast *** a result,the tentative work flow has been established, and the approach turned out to be efficient.

关键词： Concatenation Index TFIDF DCC Automatic Term Extraction unlisted term

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AUTOMATIC RECOGNITION OF CHINESE SCIENTIFIC AND TECHNOLOGICAL TERMS USING INTEGRATED LINGUISTIC knowledge

AUTOMATIC RECOGNITION OF CHINESE SCIENTIFIC AND TECHNOLOGICA...

引用

2003 international conference on natural language processing and knowledge engineering

作者： Zhifang SUI Yirong CHEN Zhouchao WEI Institute of Computational Linguistics Peking University

ISBN: (纸本)0780379020

＜正＞The paper introduces our research on using integrated linguistic knowledge to automatically recognize Chinese scientific and technological terms based on the careful analysis of the characteristics of this kind of *** system of automatic term recognition includes two phases:learning stage and application *** the stage of learning,we use a series of machine learning methods to get various kinds of integrated knowledge for automatic term recognition from a large-scale corpus and a term *** knowledge includes the inner structural knowledge of terms,the statistical domain features of term component,the statistical mutual information between the components of terms,the outer environment features of terms and the distinct text-level features of term recognition etc..In the stage of application,through an efficient model,we use all these various types of knowledge into automatic term *** experiments show that the system can give great help to the expert of term standardization to discover new terms.

关键词： Automatic Term Recognition Integrated Linguistic knowledge Machine Learning

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ZERO ANAPHORA RESOLUTION IN CHINESE WITH PARTIAL PARSING BASED ON CENTERING THEORY

ZERO ANAPHORA RESOLUTION IN CHINESE WITH PARTIAL PARSING BAS...

引用

2003 international conference on natural language processing and knowledge engineering

作者： Ching-Long Yeh Yi-Chun Chen Department of Computer Science and Engineering Tatung University 40 Chungshan N.Rd.3rd.Section Taipei 104 Taiwan China

ISBN: (纸本)0780379020

Most traditional approaches to anaphora resolution are based on the integration of complex syntactic information and domain ***,to construct a domain knowledge base is very laborintensive and *** this paper,we work on the output of a part-of-speech tagger and use a partial parsing instead of a complex parsing to resolve zero anaphors in Chinese *** employ centering theory and constraint rules to identify the antecedents of zero anaphors appeared in the preceding *** this paper,we focus on the cases of zero anaphors that occur in the topic or subject,and object positions of utterances. The result shows that the precision rates of zero anaphora detection and the recall rate of zero anaphora resolution with the method are 81%and 70%respectively.

关键词： ZERO ANAPHORA RESOLUTION IN CHINESE WITH PARTIAL PARSING BASED ON CENTERING THEORY

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