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

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Needs and challenges of care robots in nursing care setting: A literature review 护理机器人在护理环境中的需求与挑战:文献综述
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587815
Yuko Nagai, T. Tanioka, Shoko Fuji, Yuko Yasuhara, Sakiko Sakamaki, Narimi Taoka, R. Locsin, Fuji Ren, Kazuyuki Matsumoto
{"title":"Needs and challenges of care robots in nursing care setting: A literature review","authors":"Yuko Nagai, T. Tanioka, Shoko Fuji, Yuko Yasuhara, Sakiko Sakamaki, Narimi Taoka, R. Locsin, Fuji Ren, Kazuyuki Matsumoto","doi":"10.1109/NLPKE.2010.5587815","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587815","url":null,"abstract":"This study aims to identify needs and challenges of care robot in nursing care setting through an extensive search of the literature. As the result shows, there exists a shortage of information about results of the introduction of care robots, the needs of recipients and care providers, and relevant ethical problems. To advance our research and to introduce care robots into setting, there are so many things to do; consider the application of natural language processing technology by collaborating with researchers in the robotics field, carry out an investigation, extract the needs, clarify ethical problems and seek solutions, conduct the on-site experiment study, and so on.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"16 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":"132952033","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: 3
A new cascade algorithm based on CRFs for recognizing Chinese verb-object collocation 基于CRFs的汉语动宾搭配级联识别新算法
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587828
Guiping Zhang, Zhichao Liu, Qiaoli Zhou, Dongfeng Cai, Jiao Cheng
{"title":"A new cascade algorithm based on CRFs for recognizing Chinese verb-object collocation","authors":"Guiping Zhang, Zhichao Liu, Qiaoli Zhou, Dongfeng Cai, Jiao Cheng","doi":"10.1109/NLPKE.2010.5587828","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587828","url":null,"abstract":"This paper proposes a new cascade algorithm based on conditional random fields. The algorithm is applied to automatic recognition of Chinese verb-object collocation, and combined with a new sequence labeling of “ONIY”. Experiments compare identified results under two segmentations and part-of-speech tag sets. The comprehensive experimental results show that the best performance is 90.65 % in F-score over Tsinghua Treebank, and 82.00 % in F-score over the segmentation and part-of-speech tagging scheme of Peking University. Our experiments show that the proposed algorithm can greatly improve recognition accuracy of multi-nested collocation, and play a positive role on long distance collocation.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"8 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":"114551334","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: 0
Negation disambiguation using the maximum entropy model 最大熵模型的否定消歧
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587857
Chunliang Zhang, Xiaoxu Fei, Jingbo Zhu
{"title":"Negation disambiguation using the maximum entropy model","authors":"Chunliang Zhang, Xiaoxu Fei, Jingbo Zhu","doi":"10.1109/NLPKE.2010.5587857","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587857","url":null,"abstract":"Handling negation issue is of great significance for sentiment analysis. Most previous studies adopted a simple heuristic rule for sentiment negation disambiguation within a fixed context window. In this paper we present a supervised method to disambiguate which sentiment word is attached to the negator such as “(not)” in an opinionated sentence. Experimental results show that our method can achieve better performance than traditional methods.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"40 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":"117237956","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: 0
Distributed training for Conditional Random Fields 条件随机场的分布式训练
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587803
Xiaojun Lin, Liang Zhao, Dianhai Yu, Xihong Wu
{"title":"Distributed training for Conditional Random Fields","authors":"Xiaojun Lin, Liang Zhao, Dianhai Yu, Xihong Wu","doi":"10.1109/NLPKE.2010.5587803","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587803","url":null,"abstract":"This paper proposes a novel distributed training method of Conditional Random Fields (CRFs) by utilizing the clusters built from commodity computers. The method employs Message Passing Interface (MPI) to deal with large-scale data in two steps. Firstly, the entire training data is divided into several small pieces, each of which can be handled by one node. Secondly, instead of adopting a root node to collect all features, a new criterion is used to split the whole feature set into non-overlapping subsets and ensure that each node maintains the global information of one feature subset. Experiments are carried out on the task of Chinese word segmentation (WS) with large scale data, and we observed significant reduction on both training time and space, while preserving the performance.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"27 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":"123421571","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: 5
Conversion between dependency structures and phrase structures using a head finder algorithm 使用头部查找算法在依赖结构和短语结构之间进行转换
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587792
Xinxin Li, Xuan Wang, Lin Yao
{"title":"Conversion between dependency structures and phrase structures using a head finder algorithm","authors":"Xinxin Li, Xuan Wang, Lin Yao","doi":"10.1109/NLPKE.2010.5587792","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587792","url":null,"abstract":"This paper proposes how to convert projective dependency structures into flat phrase structures with language-independent syntactic categories, and use a head finder algorithm to convert these phrase structures back into dependency structures. The head finder algorithm is implemented by a maximum entropy approach with constraint information. The converted phrase structures can be parsed using a hierarchical coarse-to-fine method with latent variables. Experimental results show that the approach finds 98.8% heads of all phrases, and our algorithm achieves state-of-the-art dependency parsing performance in English Treebank.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"70 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":"127272336","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
Application of Chinese sentiment categorization to digital products reviews 中文情感分类在数字产品评论中的应用
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587788
Hongying Zan, Kuizhong Kou, Jiale Tian
{"title":"Application of Chinese sentiment categorization to digital products reviews","authors":"Hongying Zan, Kuizhong Kou, Jiale Tian","doi":"10.1109/NLPKE.2010.5587788","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587788","url":null,"abstract":"Sentiment categorization have been widely explored in many fields, such as government policy, information monitoring, product tracking, etc. This paper adopts k-NN, Naive Bayes and SVM classifiers to categorize sentiments contained in on-line Chinese reviews on digital products. Our experimental results show that combining the words and phrases with sentiment orientation as hybrid features, SWM classifier achieves an accuracy of 96,47%, which is words of all parts of speech as features.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"48 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":"127481383","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
Recognizing sentiment polarity in Chinese reviews based on topic sentiment sentences 基于主题情感句的汉语评论情感极性识别
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587863
Jiang Yang, Min Hou, Ning Wang
{"title":"Recognizing sentiment polarity in Chinese reviews based on topic sentiment sentences","authors":"Jiang Yang, Min Hou, Ning Wang","doi":"10.1109/NLPKE.2010.5587863","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587863","url":null,"abstract":"We present an approach to recognizing sentiment polarity in Chinese reviews based on topic sentiment sentences. Considering the features of Chinese reviews, we firstly identify the topic of a review using an n-gram matching approach. To extract candidate topic sentiment sentences, we compute the semantic similarity between a given sentence and the ascertained topic and meanwhile determine whether the sentence is subjective. A certain number of these sentences are then selected as representatives according to their semantic similarity value with relation to the topic. The average value of the representative topic sentiment sentences is calculated and taken as the sentiment polarity of a review. Experiment results show that the proposed method is feasible and can achieve relatively high precision.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"25 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":"126734880","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
A new algorithm of fuzzy support vector machine based on niche 基于小生境的模糊支持向量机新算法
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587796
Ying Huang, Wei Li
{"title":"A new algorithm of fuzzy support vector machine based on niche","authors":"Ying Huang, Wei Li","doi":"10.1109/NLPKE.2010.5587796","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587796","url":null,"abstract":"A new algorithm of fuzzy support vector machine based on niche is presented in this paper. In this algorithm, through comparing samples niche with class niche, the method of simply using Euclidean distance to measure the relationship of samples and class in the traditional support vector machine is changed by using the minimum radius in class niche, and the disadvantages of traditional support vector machine, which are sensitive to noise and outliers, and poor performance of differentiation of valid samples are overcome. Experimental data show that compared with the traditional support vector machine which only uses the distance between the sample and the center of class, this new algorithm can improve the convergence speed, and thus greatly enhance the discrimination between valid samples and noise samples.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"141 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":"128718342","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: 0
Term recognition using Conditional Random fields 使用条件随机场的术语识别
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-09-30 DOI: 10.1109/NLPKE.2010.5587809
Xing Zhang, Yan Song, A. Fang
{"title":"Term recognition using Conditional Random fields","authors":"Xing Zhang, Yan Song, A. Fang","doi":"10.1109/NLPKE.2010.5587809","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587809","url":null,"abstract":"A machine learning framework, Conditional Random fields (CRF), is constructed in this study, which exploits syntactic information to recognize biomedical terms. Features used in this CRF framework focus on syntactic information in different levels, including parent nodes, syntactic functions, syntactic paths and term ratios. A series of experiments have been done to study the effects of training sizes, general term recognition and novel term recognition. The experiment results show that features as syntactic paths and term ratios can achieve good precision of term recognition, including both general terms and novel terms. However, the recall of novel term recognition is still unsatisfactory, which calls for more effective features to be used. All in all, as this research studies in depth the uses of some unique syntactic features, it is innovative in respect of constructing machine learning based term recognition system.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"11 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":"116763361","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: 14
Emotion analysis in blogs at sentence level using a Chinese emotion corpus 基于中文情感语料库的博客句子情感分析
Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010) Pub Date : 2010-08-01 DOI: 10.1109/NLPKE.2010.5587790
Changqin Quan, Tingting He, F. Ren
{"title":"Emotion analysis in blogs at sentence level using a Chinese emotion corpus","authors":"Changqin Quan, Tingting He, F. Ren","doi":"10.1109/NLPKE.2010.5587790","DOIUrl":"https://doi.org/10.1109/NLPKE.2010.5587790","url":null,"abstract":"Previous researches for emotional analysis of texts have included a variety of text contents: weblogs, stories, news, text messages, spoken dialogs, and so on. Compared with other text styles, the main characteristics of emotional expressions in blogs are as follows: (1) Highly personal, subjective writing style; (2) New words and expressions are constantly emerging; (3) The integrity and continuity of using language. Using a Chinese emotion corpus (Ren-CECps), in this study, we make an analysis on emotion expressions in blogs at sentence level. Firstly, we separate the sentences into two classes: simple sentences (sentences without negative words, conjunctions, or question mark) and complex sentences (sentences with negative words, conjunctions, or question mark). Then we compare the two classes of sentence on sentence emotion recognition based on emotional words. Furthermore we analysis the following factors for emotion change at sentence level: negative words, conjunctions, punctuation marks, and contextual emotions. At last, we make an hypothesis that the emotional focus of a sentence could be expressed by a certain clause in this sentence, and the experimental results have proved this hypothesis, which showed that selecting the clauses containing emotional focus of a sentence correctly would be helpful to recognize sentence emotions.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124393457","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
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