Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680796
Wei Yang, Guang Jin, Jun Zheng, Xianliang Jiang
Due to the coupling and nonlinear relationship between processing variables, it is difficult to achieve the comprehensive optimization of injection part quality effectively only by conventional methods. To solve the problem above, firstly some quality indices were extracted according to the quality requirements of the product and a fuzzy comprehensive evaluation formula including the pertinent indices was used as a mathematical description of injection parts quality. Then an approximate calculation and optimization model was obtained by combining numerical simulation with hybrid intelligence technology. Finally the method discussed above is proved to be feasible and effective by the study of a deep-cavity and shell-shape part.
{"title":"Comprehensive optimization of injection parts quality using numerical simulation and hybrid intelligence technology","authors":"Wei Yang, Guang Jin, Jun Zheng, Xianliang Jiang","doi":"10.1109/ISKE.2010.5680796","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680796","url":null,"abstract":"Due to the coupling and nonlinear relationship between processing variables, it is difficult to achieve the comprehensive optimization of injection part quality effectively only by conventional methods. To solve the problem above, firstly some quality indices were extracted according to the quality requirements of the product and a fuzzy comprehensive evaluation formula including the pertinent indices was used as a mathematical description of injection parts quality. Then an approximate calculation and optimization model was obtained by combining numerical simulation with hybrid intelligence technology. Finally the method discussed above is proved to be feasible and effective by the study of a deep-cavity and shell-shape part.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"21 1","pages":"67-72"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76301672","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680768
E. Herrera-Viedma, Javier López Gijón, A. A. Ruiz
The aim of this paper is to present a model based on a fuzzy linguistic approach to evaluate the quality of digital libraries. The quality evaluation of digital libraries is defined using users' perceptions on the quality of digital services provided through their Web sites. We assume a fuzzy linguistic modeling to represent the users' perception and apply automatic tools of fuzzy computing with words based on the LOWA and LWA operators to compute global quality evaluations of digital libraries.
{"title":"A fuzzy linguistic quality evaluation model for digital libraries","authors":"E. Herrera-Viedma, Javier López Gijón, A. A. Ruiz","doi":"10.1109/ISKE.2010.5680768","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680768","url":null,"abstract":"The aim of this paper is to present a model based on a fuzzy linguistic approach to evaluate the quality of digital libraries. The quality evaluation of digital libraries is defined using users' perceptions on the quality of digital services provided through their Web sites. We assume a fuzzy linguistic modeling to represent the users' perception and apply automatic tools of fuzzy computing with words based on the LOWA and LWA operators to compute global quality evaluations of digital libraries.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"1 1","pages":"640-645"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82581154","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680880
Hao Huang, Shuoping Wang, Lianhang Ma
Identification of useful anomalies is an emerging task in active learning scenario. It plays the central roles in category detection in which one can using a sampling approach to label a data from rare category in an unlabeled date set by the help of the oracle who has a small querying budget. This paper presents an enhanced category detection that improves previous research work which leans to cost more querying budget. The new approach takes full advantage of the feedback of the oracle, and reduces the querying times. Experimental results on both synthetic and real data sets are effective and low-cost.
{"title":"An enhanced category detection based on active learning","authors":"Hao Huang, Shuoping Wang, Lianhang Ma","doi":"10.1109/ISKE.2010.5680880","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680880","url":null,"abstract":"Identification of useful anomalies is an emerging task in active learning scenario. It plays the central roles in category detection in which one can using a sampling approach to label a data from rare category in an unlabeled date set by the help of the oracle who has a small querying budget. This paper presents an enhanced category detection that improves previous research work which leans to cost more querying budget. The new approach takes full advantage of the feedback of the oracle, and reduces the querying times. Experimental results on both synthetic and real data sets are effective and low-cost.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"5 1","pages":"224-227"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83588773","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680782
R. Lu
This paper reviews the basic concepts of knowware engineering and proposes a methodology of object-oriented knowware analysis. Also a preliminary framework of abstract semantics for knowware programming is studied. We propose the technique of symbolic generator and symbolic inheritance to implement the abstract interpretation of class methods and class inheritance when concrete and abstract objects and classes both exist.
{"title":"Object-oriented knowware programming and its abstract inheritance semantics","authors":"R. Lu","doi":"10.1109/ISKE.2010.5680782","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680782","url":null,"abstract":"This paper reviews the basic concepts of knowware engineering and proposes a methodology of object-oriented knowware analysis. Also a preliminary framework of abstract semantics for knowware programming is studied. We propose the technique of symbolic generator and symbolic inheritance to implement the abstract interpretation of class methods and class inheritance when concrete and abstract objects and classes both exist.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85971817","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680872
Feng Wang, Dexian Zhang, Lichun Man, Junwei Yu
To improve accuracy and adaptability, this paper presents a learning algorithm for color recognition of license plates. For three components of the hue-saturation-value (HSV) color space, different membership functions were defined to calculate their fuzzy degrees. Through the weighted fusion of the three membership degrees, a single map was produced to be the classification function for color recognition, and the final decision is based on the integrated map. Thresholds of membership functions, weight vectors of membership degrees and classification thresholds were all learned by the proposed learning algorithm, according to the classification error minimization inductive principle. Experiments were conducted on two different test sets. The overall accuracies of the proposed algorithm are 97.70% and 96.20%, respectively. The experimental results show that the proposed algorithm can learn the appropriate thresholds and weights from the training images, which are consistent with the practical application environments. Thus it improves the accuracy and adaptability of the color recognition algorithm and can meet the requirements of the practical engineering applications.
{"title":"Learning algorithm for color recognition of license plates","authors":"Feng Wang, Dexian Zhang, Lichun Man, Junwei Yu","doi":"10.1109/ISKE.2010.5680872","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680872","url":null,"abstract":"To improve accuracy and adaptability, this paper presents a learning algorithm for color recognition of license plates. For three components of the hue-saturation-value (HSV) color space, different membership functions were defined to calculate their fuzzy degrees. Through the weighted fusion of the three membership degrees, a single map was produced to be the classification function for color recognition, and the final decision is based on the integrated map. Thresholds of membership functions, weight vectors of membership degrees and classification thresholds were all learned by the proposed learning algorithm, according to the classification error minimization inductive principle. Experiments were conducted on two different test sets. The overall accuracies of the proposed algorithm are 97.70% and 96.20%, respectively. The experimental results show that the proposed algorithm can learn the appropriate thresholds and weights from the training images, which are consistent with the practical application environments. Thus it improves the accuracy and adaptability of the color recognition algorithm and can meet the requirements of the practical engineering applications.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"53 1","pages":"238-243"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88374954","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680859
Gang Li, Fei Liu
This paper introduces the clustering-based sentiment analysis approach which is a new approach to sentiment analysis. By applying a TF-IDF weighting method, voting mechanism and importing term scores, an acceptable and stable clustering result can be obtained. It has competitive advantages over the two existing kinds of approaches: symbolic techniques and supervised learning methods. It is a well performed, efficient, and non-human participating approach on solving sentiment analysis problems.
{"title":"A clustering-based approach on sentiment analysis","authors":"Gang Li, Fei Liu","doi":"10.1109/ISKE.2010.5680859","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680859","url":null,"abstract":"This paper introduces the clustering-based sentiment analysis approach which is a new approach to sentiment analysis. By applying a TF-IDF weighting method, voting mechanism and importing term scores, an acceptable and stable clustering result can be obtained. It has competitive advantages over the two existing kinds of approaches: symbolic techniques and supervised learning methods. It is a well performed, efficient, and non-human participating approach on solving sentiment analysis problems.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"91 1","pages":"331-337"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85829894","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680833
Kejing Zhang, Huilin Chen, Changjun Dai
This paper seeks to explore the influencing mechanism of IT on the productivity of knowledge work. Firstly, based on the analysis of the existing research, the key characteristics of IT, knowledge work and its productivity are defined. Secondly, a three layer conceptual model is proposed. With a questionnaire designed for the empirical study and the data collected, a mathematical model for the analysis of the effects of IT on knowledge work productivity is built by applying structural equation modeling. LISREL8.70 is used to do the path analysis. For the questionnaire, reliability and validity analysis have been provided. The mathematical model consisting of measurement model and structure model are obtained, which explains the relationship among the dimensions of IT, knowledge work and its productivity.
{"title":"Research on the effects of information technology on knowledge work productivity","authors":"Kejing Zhang, Huilin Chen, Changjun Dai","doi":"10.1109/ISKE.2010.5680833","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680833","url":null,"abstract":"This paper seeks to explore the influencing mechanism of IT on the productivity of knowledge work. Firstly, based on the analysis of the existing research, the key characteristics of IT, knowledge work and its productivity are defined. Secondly, a three layer conceptual model is proposed. With a questionnaire designed for the empirical study and the data collected, a mathematical model for the analysis of the effects of IT on knowledge work productivity is built by applying structural equation modeling. LISREL8.70 is used to do the path analysis. For the questionnaire, reliability and validity analysis have been provided. The mathematical model consisting of measurement model and structure model are obtained, which explains the relationship among the dimensions of IT, knowledge work and its productivity.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"2 1","pages":"464-469"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84991136","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680772
Fatma Aksu, K. Vanhoof, L. Munck
This paper focuses on small and midsized enterprises (SME's) and investigates which business process modeling (BPM) methodology is the most adequate and appropriate for these type of companies. Therefore, it selects and applies a general framework along with the evaluation and comparison of BPM-methodologies rather than isolated frameworks. More specific, this paper emphasizes the intention towards a foundation of such a framework based on a method ranking approach combined with a case based approach.
{"title":"Evaluation and comparison of business process modeling methodologies for small and midsized enterprises","authors":"Fatma Aksu, K. Vanhoof, L. Munck","doi":"10.1109/ISKE.2010.5680772","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680772","url":null,"abstract":"This paper focuses on small and midsized enterprises (SME's) and investigates which business process modeling (BPM) methodology is the most adequate and appropriate for these type of companies. Therefore, it selects and applies a general framework along with the evaluation and comparison of BPM-methodologies rather than isolated frameworks. More specific, this paper emphasizes the intention towards a foundation of such a framework based on a method ranking approach combined with a case based approach.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"13 1","pages":"664-667"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83172137","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680839
Michael Robertson, Yin Pan, Bo Yuan
In the midst of a social networking revolution, social media has become the new vehicle for effective business marketing and transactions. As social aspects to the Internet continue to expand in both quantity and scope, so has the security threat towards enterprise networks and systems. Many social networking users also become main targets of spams, phishing, stalking, and other malware attacks that exploit the trust among social network “friends”. This paper presents a comprehensive method combining traditional security heuristics with social networking data to aid in the detection of malicious web content as it propagates through the user's network. A Facebook application is implemented to automatically evaluate and detect malicious link content. The results of testing this application against known phishing and malware sites with real-world user profiles have shown encouraging results.
{"title":"A social approach to security: Using social networks to help detect malicious web content","authors":"Michael Robertson, Yin Pan, Bo Yuan","doi":"10.1109/ISKE.2010.5680839","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680839","url":null,"abstract":"In the midst of a social networking revolution, social media has become the new vehicle for effective business marketing and transactions. As social aspects to the Internet continue to expand in both quantity and scope, so has the security threat towards enterprise networks and systems. Many social networking users also become main targets of spams, phishing, stalking, and other malware attacks that exploit the trust among social network “friends”. This paper presents a comprehensive method combining traditional security heuristics with social networking data to aid in the detection of malicious web content as it propagates through the user's network. A Facebook application is implemented to automatically evaluate and detect malicious link content. The results of testing this application against known phishing and malware sites with real-world user profiles have shown encouraging results.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"61 1","pages":"436-441"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89703207","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}
Pub Date : 2010-11-01DOI: 10.1109/ISKE.2010.5680852
Shuang Song, Li Yu, Xiaoping Yang
The success and popularity of collaborative tagging systems, such as delicious1, Flickr2, Last.fm3, has increasingly centered on. Users of these websites can easily tag their interested WebPages, photos and music with their preferred words. Subsequently, the extensive tagging data attract many researchers to mine useful information from these. In this paper, we propose a novel user interests quantified approach based on user-generated tags. Moreover, by means of the generative probabilistic model Latent Dirichlet Allocation (LDA), we acquire the interests for each user. Experimenting with the dataset provided within the ECML PKDD Discovery Challenge 2009, our method makes better performance.
{"title":"LDA-based user interests discovery in collaborative tagging system","authors":"Shuang Song, Li Yu, Xiaoping Yang","doi":"10.1109/ISKE.2010.5680852","DOIUrl":"https://doi.org/10.1109/ISKE.2010.5680852","url":null,"abstract":"The success and popularity of collaborative tagging systems, such as delicious1, Flickr2, Last.fm3, has increasingly centered on. Users of these websites can easily tag their interested WebPages, photos and music with their preferred words. Subsequently, the extensive tagging data attract many researchers to mine useful information from these. In this paper, we propose a novel user interests quantified approach based on user-generated tags. Moreover, by means of the generative probabilistic model Latent Dirichlet Allocation (LDA), we acquire the interests for each user. Experimenting with the dataset provided within the ECML PKDD Discovery Challenge 2009, our method makes better performance.","PeriodicalId":6417,"journal":{"name":"2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering","volume":"1 1","pages":"338-343"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89819840","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}
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