2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)最新文献_第6页

An efficient feature selection paradigm using PCA-CFS-Shapley values ensemble applied to small medical data sets 一种基于PCA-CFS-Shapley值集成的高效特征选择范式，应用于小型医疗数据集

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726773

S. Sasikala, S. Appavu alias Balamurugan, S. Geetha

{"title":"An efficient feature selection paradigm using PCA-CFS-Shapley values ensemble applied to small medical data sets","authors":"S. Sasikala, S. Appavu alias Balamurugan, S. Geetha","doi":"10.1109/ICCCNT.2013.6726773","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726773","url":null,"abstract":"The precise diagnosis of patient profiles into categories, such as presence or absence of a particular disease along with its level of severity, remains to be a crucial challenge in biomedical field. This process is realized by the performance of the classifier by using a supervised training set with labeled samples. Then based on the result obtained, the classifier is allowed to predict the labels of new samples. Due to presence of irrelevant features it is difficult for standard classifiers from obtaining good detection rates. Hence it is important to select the features which are more relevant and by with good classifiers could be constructed to obtain a good accuracy and efficiency. This study is aimed to classify the medical profiles, and is realized by feature extraction (FE), feature ranking (FR) and dimension reduction methods (Shapley Values Analysis) as a hybrid procedure to improve the classification efficiency and accuracy. To appraise the success of the proposed method, experiments were conducted across 6 different medical data sets using J48 decision tree classifier. The experimental results showed that using the PCA-CFS-Shapley Values analysis procedure improves the classification efficiency and accuracy compared with individual usage.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"276 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85211778","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: 4

Investigating the factors responsible for hepatitis disease using rough set theory 用粗糙集理论研究肝炎疾病的致病因素

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6850237

Archit Gupta, Sanjiban Sekhar Roy, Sanchit Sabharwal, Rajat Gupta

引用次数: 0

A system to filter unsolicited texts from social learning networks 一个从社交学习网络中过滤未经请求的文本的系统

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726687

S. Yadav, S. Das, D. Rudrapal

{"title":"A system to filter unsolicited texts from social learning networks","authors":"S. Yadav, S. Das, D. Rudrapal","doi":"10.1109/ICCCNT.2013.6726687","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726687","url":null,"abstract":"In the present day scenario online social networks (OSN) are very trendy and one of the most interactive medium to share, communicate and exchange numerous types of information like text, image, audio, video etc. All these publicly shared information are explicitly viewed by connected people in the blog or networks and having an enormous social impact in human mind. Posting or commenting on particular public/private areas called wall, may include superfluous messages or sensitive data. Information filtering can therefore have a solid influence in online social networks and it can be used to give users the facility to organize the messages written on public areas by filtering out unwanted wordings. In this paper, we have proposed a system which may allow OSN users to have a direct control on posting or commenting on their walls with the help of information filtering. This is achieved through text pattern matching system, that allows users to filter their open space and a privilege to add new words treated as unwanted. For experimental analysis a test social learning website is designed and some unwanted words/texts are kept as blacklisted vocabulary. To provide control to the user, pattern matching of texts are done with the blacklisted vocabulary. If it passes then only text can be posted on someone's wall, otherwise text will be blurred or encoded with special symbols. Analysis of experimental results shows high accuracy of the proposed system.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81678462","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: 4

A UPnP extension for multilevel security in pervasive systems 普适系统中多层安全的UPnP扩展

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726733

P. Rajkumar, A. Nair

引用次数: 1

An artificial immune system with local feature selection classifier for spam filtering 基于局部特征选择分类器的人工免疫系统垃圾邮件过滤

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726691

Mayank Kalbhor, S. Shrivastava, Babita Ujjainiya

{"title":"An artificial immune system with local feature selection classifier for spam filtering","authors":"Mayank Kalbhor, S. Shrivastava, Babita Ujjainiya","doi":"10.1109/ICCCNT.2013.6726691","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726691","url":null,"abstract":"The Local Concentration based feature extraction approach is take into consideration to be able to very effectively extract position related information from messages by transforming every area of a message to a corresponding LC feature. To include the LC approach into the entire process of spam filtering, a LC model is designed, where two kinds of detector sets are initially generated by using term selection strategies and a well-defined tendency threshold, then a window is applied to divide the message into local areas. After segmentation of the particular message, concentration of the detectors are calculated and brought as the feature for every local area. Finally, feature vector is created by combining all the local feature area. Then appropriate classification method inspired from immune system is applied on available feature vector. To check the performance of model, several experiments are conducted on four benchmark corpora using the cross-validation methodology. It is shown that our model performs well with the Information Gain as term selection methods, LC based feature extraction method with flexible applicability in the real world. In comparison of other global-concentration based feature extraction techniques like bag-of-word the LC approach has better performance in terms of both accuracy and measure. It is also demonstrated that the LC approach with artificial immune system inspired classifier gives better results against all parameters.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"382 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83765133","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

An efficient query processing with approval of data reliability using RBF neural networks with web enabled data warehouse 基于web数据仓库的RBF神经网络的高效查询处理和数据可靠性验证

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726845

K. Soundararajan, Dr. S. Sureshkumar, P. Selvamani

{"title":"An efficient query processing with approval of data reliability using RBF neural networks with web enabled data warehouse","authors":"K. Soundararajan, Dr. S. Sureshkumar, P. Selvamani","doi":"10.1109/ICCCNT.2013.6726845","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726845","url":null,"abstract":"To rise above the limitation of the Traditional load forecasting method using data warehousing system, a new load forecasting system basing on Radial Basis Gaussian kernel Function (RBF) neural network is proposed in this project. Genetic algorithm adopting the actual coding, crossover and mutation probability was applied to optimize the parameters of the neural network, and a faster growing rate was reached. Theoretical analysis and models prove that this model has more accuracy than the traditional one. There are several methods available to integrate information source, but only few methods focus on evaluating the reliability of the source and its information. The emergence of the web and dedicated data warehouses offer different kinds of ways to collect additional data to make better decisions. The reliable and trust of these data depends on many different aspects and metainformation: data source, experimental protocol. Developing generic tools to evaluate this reliability represents a true challenge for the proper use of distributed data. In this project, RBF neural network based approach to evaluate data reliability from a set of criteria has been proposed. Customized criteria and intuitive decisions are provided, information reliability and reassurance are most important components of a data warehousing system, as their power in a while retrieval and examination.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"81 3 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83154664","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

Optimized data analysis in cloud using BigData analytics techniques 使用大数据分析技术优化云中的数据分析

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726631

Mr. S. Ramamoorthy, Dr. S. Rajalakshmi

{"title":"Optimized data analysis in cloud using BigData analytics techniques","authors":"Mr. S. Ramamoorthy, Dr. S. Rajalakshmi","doi":"10.1109/ICCCNT.2013.6726631","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726631","url":null,"abstract":"Because of the huge reduce in the overall investment and greatest flexibility provided by the cloud, all the companies are nowadays migrating their applications towards cloud environment. Cloud provides the larger volume of space for the storage and different set of services for all kind of applications to the cloud users without any delay and not required any major changes at the client level. When the large amount of user data and application results stored on the cloud environment, will automatically make the data analysis and prediction process became very difficult on the different clusters of cloud. Whenever the used required to analysis the stored data as well as frequently used services by other cloud customers for the same set of query on the cloud environment hard to process. The existing data mining techniques are insufficient to analyse those huge data volumes and identify the frequent services accessed by the cloud users. In this proposed scheme trying to provide an optimized data and service analysis based on Map-Reduce algorithm along with BigData analytics techniques. Cloud services provider can Maintain the log for the frequent services from the past history analysis on multiple clusters to predict the frequent service. Through this analysis cloud service provider can able to recommend the frequent services used by the other cloud customers for the same query. This scheme automatically increase the number of customers on the cloud environment and effectively analyse the data which is stored on the cloud storage.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"98 6 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83234329","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: 18

A novel boundary approach for shape representation and classification 一种新的形状表示与分类边界方法

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726673

L. Sumalatha, B. Sujatha, P. Sreekanth

引用次数: 0

Fuzzy based clustering method on yeast dataset with different fuzzification methods 采用不同模糊化方法对酵母数据集进行模糊聚类

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726574

P. Ashok, G. M. Kadhar, E. Elayaraja, V. Vadivel

{"title":"Fuzzy based clustering method on yeast dataset with different fuzzification methods","authors":"P. Ashok, G. M. Kadhar, E. Elayaraja, V. Vadivel","doi":"10.1109/ICCCNT.2013.6726574","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726574","url":null,"abstract":"Clustering is a process for classifying objects or patterns in such a way that samples of the same group are more similar to one another than samples belonging to different groups. In this paper, we introduce the clustering method called soft clustering and its type Fuzzy C-Means. The clustering algorithms are improved by implementing the two different membership functions. The Fuzzy C-Means algorithm can be improved by implementing the Fuzzification parameter values from 1.25 to 2.0 and compared with different datasets using Davis Bouldin Index. The Fuzzification parameter 2.0 is most suitable for Fuzzy C-Means clustering algorithm than other Fuzzification parameter. The Fuzzy C-Means and K-Means clustering algorithms are implemented and executed in Matlab and compared with Execution speed and Iteration Count Methods. The Fuzzy C-Means clustering method achieve better results and obtain minimum DB index for all the different cluster values from different datasets. The experimental results shows that the Fuzzy C-Means method performs well when compare with the K-Means clustering.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"117 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83440296","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

Hybrid technique for user's web page access prediction based on Markov model 基于马尔可夫模型的用户网页访问预测混合技术

2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT) Pub Date : 2013-07-04 DOI: 10.1109/ICCCNT.2013.6726588

Priyank Panchal, Urmi D. Agravat

{"title":"Hybrid technique for user's web page access prediction based on Markov model","authors":"Priyank Panchal, Urmi D. Agravat","doi":"10.1109/ICCCNT.2013.6726588","DOIUrl":"https://doi.org/10.1109/ICCCNT.2013.6726588","url":null,"abstract":"Web Mining consists of three different categories, namely Web Content Mining, Web Structure Mining, and Web Usage Mining (is the process of discovering knowledge from the interaction generated by the users in the form of access logs, browser logs, proxy-server logs, user session data, cookies). This paper present mining process of web server log files in order to extract usage patterns to web link prediction with the help of proposed Markov Model. The approaches result in prediction of popular web page or stage and user navigation behavior. Proposed technique cluster user navigation based on their pair-wise similarity measure combined with markov model with the concept of apriori algorithm which is used for Web link prediction is the process to predict the Web pages to be visited by a user based on the Web pages previously visited by other user. So that Web pre-fetching techniques reduces the web latency & they predict the web object to be pre-fetched with high accuracy and good scalability also help to achieve better predictive accuracy among different log file The evolutionary approach helps to train the model to make predictions commensurate to current web browsing patterns.","PeriodicalId":6330,"journal":{"name":"2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)","volume":"75 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2013-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78873978","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: 10