Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)最新文献_第3页

A pragmatic model for new Chinese word extraction 汉语新词提取的语用模型

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587846

Haijun Zhang, Heyan Huang, Chao-Yong Zhu, Shumin Shi

引用次数: 7

Image understanding for converting images into natural language text sentences 将图像转换为自然语言文本句子的图像理解

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587864

N. Bourbakis

{"title":"Image understanding for converting images into natural language text sentences","authors":"N. Bourbakis","doi":"10.1109/NLPKE.2010.5587864","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587864","url":null,"abstract":"The efficient processing, association and understanding of multimedia based events or multi-modal information is a very important research field with a great variety of applications, such as knowledge discovery, document understanding, human computer interaction, etc. A good approach to this important issue is the development of a common platform for converting different modalities (such as images, text, etc) into the same medium and associating them for efficient processing and understanding. Thus, this talk here presents the development of a methodology capable for automatically converting images into natural language (NL) text sentences using image processing-analysis methods and graphs with attributes for object recognition, and image understanding. Then it converts graph representations into NL text sentences. Moreover, it presents a methodology for transforming NL sentences into Graph representations and then into Stochastic Petri-nets (SPN) descriptions in order to offer a common model of representation of multimodal information and at the same time a way of associating “activities or changes” in image frames for events representation and interpretation. The selection of the SPN graph model is due to its capability for efficiently representing structural and functional knowledge where other models cannot. Simple illustrative examples are provided for proving the concept presented here.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131050916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Pragmatic analysis based query expansion for Chinese cuisine QA service system 基于语用分析的中餐问答服务系统查询扩展

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587785

Ling Xia, F. Ren

引用次数: 0

Context-based term identification and extraction for ontology construction 面向本体构建的基于上下文的术语识别与提取

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587801

Hui-Ngo Goh, Ching Kiu

{"title":"Context-based term identification and extraction for ontology construction","authors":"Hui-Ngo Goh, Ching Kiu","doi":"10.1109/NLPKE.2010.5587801","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587801","url":null,"abstract":"Ontology construction often requires a domain specific corpus in conceptualizing the domain knowledge; specifically, it is an association of terms, relation between terms and related instances. It is a vital task to identify a list of significant term for constructing a practical ontology. In this paper, we present the use of a context-based term identification and extraction methodology for ontology construction from text document. The methodology is using a taxonomy and Wikipedia to support automatic term identification and extraction from structured documents with an assumption of candidate terms for a topic are often associated with its topic-specific keywords. A hierarchical relationship of super-topics and sub-topics is defined by a taxonomy, meanwhile, Wikipedia is used to provide context and background knowledge for topics that defined in the taxonomy to guide the term identification and extraction. The experimental results have shown the context-based term identification and extraction methodology is viable in defining topic concepts and its sub-concepts for constructing ontology. The experimental results have also proven its viability to be applied in a small corpus / text size environment in supporting ontology construction.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126280720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Co-construction of ontology-based knowledge base through the Web: Theory and practice 基于本体的Web知识库协同构建:理论与实践

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587804

Keliang Zhang, Qinlong Fei

引用次数: 0

A combination method of CRF with syntactic rules to identify opinion_holder 一种结合CRF和语法规则来识别opinion_holder的方法

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587848

Yuan Kuang, Yanquan Zhou, Huacan He

引用次数: 3

Syntactic correlations of prosodic phrase in broadcasting news speech 广播新闻讲话中韵律短语的句法关联

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587770

Yu Zou, Jiyuan Wu, W. He, Min Hou, Yonglin Teng

引用次数: 1

A study on disambiguation of structure “prep+n1+de+n2” for Chinese information processing 汉语信息处理中“prep+n1+de+n2”结构的消歧研究

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587784

Song Gao, Yiyi Zhao, Haitao Liu, Zhiwei Feng

引用次数: 0

Identifying emotion topic — An unsupervised hybrid approach with Rhetorical Structure and Heuristic Classifier 情感主题识别——一种基于修辞结构和启发式分类器的无监督混合方法

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587777

Dipankar Das, Sivaji Bandyopadhyay

{"title":"Identifying emotion topic — An unsupervised hybrid approach with Rhetorical Structure and Heuristic Classifier","authors":"Dipankar Das, Sivaji Bandyopadhyay","doi":"10.1109/NLPKE.2010.5587777","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587777","url":null,"abstract":"This paper describes an unsupervised hybrid approach to identify emotion topic(s) from English blog sentences. The baseline system is based on object related dependency relations from parsed constituents. However, the inclusion of the topic related thematic roles present in the verb based syntactic argument structure improves the performance of the baseline system. The argument structures are extracted using VerbNet. The unsupervised hybrid approach consists of two phases; firstly, the information of Rhetorical Structure (RS) is extracted to identify the target span corresponding to the emotional expression from each sentence. Secondly, as an individual target span contains one or more topics corresponding to an emotional expression, a Heuristic Classifier (HC) is designed to identify each of the topic spans associated in the target span. The classifier uses the information of Emotion Holder (EH), Named Entities (NE) and four types of Similarity features to identify the phrase level components of the topic spans. The system achieves average recall, precision and F-score of 60.37%, 57.49% and 58.88% respectively with respect to all emotion classes on 500 annotated sentences containing single or multiple emotion topics.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129041439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Weakly supervised relevance feedback based on an improved language model 基于改进语言模型的弱监督相关反馈

Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587859

Xinsheng Li, Si Li, Weiran Xu, Guang Chen, Jun Guo

引用次数: 0