Jike Ge, Zuqin Chen, Jun Peng, Taifu Li, Long Zhang
{"title":"Web service recommendation based on QoS prediction method","authors":"Jike Ge, Zuqin Chen, Jun Peng, Taifu Li, Long Zhang","doi":"10.1109/COGINF.2010.5599757","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599757","url":null,"abstract":"The realization of the Semantic Web is underway with the development of an arena of services providing similar properties, capabilities, interfaces, and effects. To pick one of such similar and useful services that matches the user's requirements is a difficult task and necessitates the use of an intelligent decision making framework. This paper proposes a QoS prediction method used to recommend Web service for solving the problem of choosing high quality Web service. According to the different feeling of different users to the same service, and the different similarity among the QoS of different services, the approach first divides the users and services into several modes, and then calculates the means of one mode to predict the QoS of a service that the user never used before. Experimental simulation results show that with this approach the preciseness of QoS prediction for Web services can be improved significantly.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129962191","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}
{"title":"Predicting RNA secondary structure with Tabu Search","authors":"Yongguo Liu, Jianrui Hao, Jun Peng","doi":"10.1109/COGINF.2010.5599703","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599703","url":null,"abstract":"In this paper, a novel method for predicting RNA secondary structure called RNA secondary structure prediction based on Tabu Search (RNATS) is proposed. In RNATS, two search models, intensification search and diversification search, are designed to exploit the local regions around the current solution and explore the unvisited space, respectively. Simulation experiments are conducted for six RNA sequences to show that the proposed method is feasible and effective.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129972396","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}
{"title":"CM-HMM: Inter-residue contact and HMM-profiles based enzyme subfamily prediction and structure analysis","authors":"Siriwon Taewijit, Kitsana Waiyamai","doi":"10.1109/COGINF.2010.5599792","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599792","url":null,"abstract":"Enzyme family prediction is extensively used to identify new family members. It is well known that enzyme function is strongly related to its structure. In this work, we proposed a novel approach, CM-HMM, to predict enzyme subfamily which yielded high accuracy when sequence similarity is less than 30%. Moreover, it provided descriptive information for 3-dimensional analysis. Our method used information from residue contact map, representative matrix of a contact between 2 residues on 3-dimensional domain which implies a contact between secondary structures, and HMM-profiles. In addition, binding or catalytic site regions were used to improve accuracy. Therefore only proteins having PDB structure can be used to be representative feature of protein sequence. The challenge was increased when we found that only 11.21% of standard dataset have PDB structures. Empirical results using a support vector machine showed that CM-HMM yielded 73.71% accuracy by jackknife test and 79.24% accuracy for an independent dataset test. Furthermore, the result can exhibit approximate protein structure based on contact map. Each structure which is laid on each position of contact map is directly related to its function. This information can help researcher understand the underlying of unknown enzyme. These suggest that CM-HMM's feature extraction from contact map and HMM-profiles are sufficiently significant for enzyme subfamily classification.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130901666","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}
{"title":"Some features of transmission mechanisms in Bulletin Board System","authors":"Weijie Li, Hongyun Bao","doi":"10.1109/COGINF.2010.5599816","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599816","url":null,"abstract":"Herding in humans is a form of convergent social behavior and one of trends in cognitive sciences. One of issues on herding is transmission mechanisms of thoughts or behaviour between agents, which affects the cognitive abilities of group or organization. In this paper, we try to analyze transmission mechanisms in Bulletin Board System (BBS). BBS is one of the most popular mediums of communication and information on the World Wide Web (WWW) in China. We model a tree structure emergent from reply relationship for BBS. Our analysis aims to answer three key questions: (a) what are properties of each post? (b) what can we find about the size distribution of cascades? and (c) do graphs of information cascades have common shapes? Experimental results prove that: (a) a large number of people just browse or reply a small number of posts, (b) the number of posts vs. the number of replies and the number of posts vs. the range of view count both obey the power-law distribution.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126708468","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}
{"title":"Using space syntax to understand knowledge acquisition and wayfinding in indoor environments","authors":"Rui Li, A. Klippel","doi":"10.1109/COGINF.2010.5599724","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599724","url":null,"abstract":"It is critical to understand how characteristics of environment influence human acquisition of spatial knowledge and wayfinding behaviors. The understanding provides insights for designing cognitively ergonomic wayfinding aids. Space syntax has been increasingly used in applications such as formal descriptions of environments and predicating wayfinding behaviors. From the perspective of cognitive geography, we review two popularly used methods of space syntax and relate them to the legibility of the environment. That is, how the elements of the environment aid the acquisition of spatial knowledge. The five elements of built environments in cognitive maps and the legibility of the environment are used as the theoretical frame to review each method. An exploratory behavioral experiment is designed to validate the formal descriptions produced by space syntax. Results indicate that different methods of space syntax have specific strengths on understanding knowledge acquisition and wayfinding behaviors in environment. Further directions of improving space syntax are also discussed.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121172787","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}
{"title":"From consumer perception characterization to human centered industrial product design","authors":"Xianyi Zeng, L. Koehl","doi":"10.1109/COGINF.2010.5599762","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599762","url":null,"abstract":"In this paper, we present a general approach for helping designers to develop new human centered industrial products using intelligent techniques. First, we characterize and evaluate consumer perception on industrial products, which is composed of two levels: basic perception independent of the socio-cultural context of these products, and complex socio-cultural concepts integrated into these products. The related human evaluation data are modeled and analyzed using fuzzy sets. Next, the complex relations between these two levels of perception as well as the physical design parameters of industrial products are modeled using decision trees and a fuzzy cognitive map. The decision trees are used for setting up an empirical model from learning data measured and evaluated on a set of representative samples while the fuzzy cognitive map permits to build a conceptual model from professional knowledge of experts. These models are then combined so that these two different information sources can be used in a complementary way in order to form a more complete model. Based on these models, we can analyze relations of products and consumers in order to obtain a suitable market segmentation and find relevant product parameters according to specific requirements of consumers at different levels.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116677704","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}
{"title":"Modeling Gestalt laws for classification","authors":"Guihua Wen, Xingjiang Pan, Lijun Jiang, Jun Wen","doi":"10.1109/COGINF.2010.5599779","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599779","url":null,"abstract":"The k-nearest neighbors classifier is simple and often results in good classification performance on problems with unknown and non-normal distributions. However, its selected nearest neighbors on noisy, sparse, or imbalanced data are often inconsistent with our intuition and in turn leads to the worse performance. This paper applies Gestalt visual perceptual laws to design a new KNN classifie r. It applies the neighborhood relation between any two data points to construct the geometry shape of data and then applies the Gestalt laws on this shape to perform the classification. The conducted experiments on challenging benchmark real data validate the proposed approach.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125172747","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}
A. Kharrat, Karim Gasmi, M. B. Messaoud, Nacéra Benamrane, M. Abid
{"title":"Automated classification of magnetic resonance brain images using Wavelet Genetic Algorithm and Support Vector Machine","authors":"A. Kharrat, Karim Gasmi, M. B. Messaoud, Nacéra Benamrane, M. Abid","doi":"10.1109/COGINF.2010.5599712","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599712","url":null,"abstract":"In this paper we propose a new approach for automated diagnosis and classification of Magnetic Resonance (MR) human brain images, using Wavelets Transform (WT) as input to Genetic Algorithm (GA) and Support Vector Machine (SVM). The proposed method segregates MR brain images into normal and abnormal. Our contribution employs genetic algorithm for feature selection witch requires much lighter computational burden. An excellent classification rate of 100% could be achieved using the support vector machine. We observe that our results are significantly better than the results reported in a previous research work employing Wavelet Transform and Support Vector Machine.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122667494","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}
{"title":"A fuzzy method designed to improve riding comfort and handling safety of engineering vehicle","authors":"J. Sun, A. Zhu","doi":"10.1109/COGINF.2010.5599758","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599758","url":null,"abstract":"With the user's needs and the development of modern technology, the engineering vehicles develop continuously toward the heavy-load and high-speed direction. The higher riding comfort requirements of engineering vehicles are put forward. The traditional passive suspension had not met the requirements of riding comfort. An adaptive fuzzy PID control method is proposed for the semi-active suspension model of engineering vehicle. The engineering vehicles are taken as the study objects, and an adaptive fuzzy PID controller is designed for improving riding comfort and handling safety. The performance indexes of the semi-active suspension system with adaptive fuzzy PID control strategy have different degree improvements. Therefore, the results are beneficial to the design and development of next generation of engineering vehicles.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131407411","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}
{"title":"Design of an intelligent support agent model for people with a cognitive vulnerability","authors":"A. A. Aziz, M. Klein","doi":"10.1109/COGINF.2010.5599725","DOIUrl":"https://doi.org/10.1109/COGINF.2010.5599725","url":null,"abstract":"This paper presents the design of an intelligent agent application aimed at supporting people with a cognitive vulnerability to prevent the onset of a depression. For this, a computational model of the cognitive processes around depression is used. The agent application uses the principles of Rational Emotive Behavioural Therapy. The effect of the application is studied using software simulation. The simulation shows that a person that responds to REBT therapy develops less cognitive vulnerability than people that are not supported.","PeriodicalId":365083,"journal":{"name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133174035","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}