2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)最新文献_第6页

A choice based recommendation system using WUM and clustering 基于WUM和聚类的基于选择的推荐系统

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684116

Deptii D. Chaudhari, N. Agnihotri, Shreejith Nair, Pankaj Dandwani, Swapnil Kulange

引用次数: 1

A novel CBIR system based on combination of color moment and Gabor filter 一种基于颜色矩与Gabor滤波器相结合的新型CBIR系统

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684169

Muhsina Kaipravan, R. Rejiram

引用次数: 12

An optimal weighted cluster based routing protocol for MANET 基于加权聚类的最优MANET路由协议

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684122

Aswathy P. Sreevatsan, Diya Thomas

{"title":"An optimal weighted cluster based routing protocol for MANET","authors":"Aswathy P. Sreevatsan, Diya Thomas","doi":"10.1109/SAPIENCE.2016.7684122","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684122","url":null,"abstract":"A MANET is an ad hoc network that can change locations and configure itself dynamically. The link breakage between the nodes due to their movement makes the routing in MANET a difficult process. Grouping the nodes into different clusters can make the task of routing in the network easier. A cluster head is a node present in the geographical region of the cluster and also takes care of the routing and allocation of resources for the cluster members. Nodes register themselves with the cluster head to become members of the cluster. Most clustering algorithms take into account only one factor for clustering. The weighted clustering algorithm takes into account a number of factors such as mobility, degree, battery power and distance to neighbors for clustering process. After clustering the path between any two nodes consists of only clusterheads and gateways of the clusters in the path. This leads to long lived paths between any two nodes. The association and dissociation of nodes to and from clusters perturb the stability of the network topology, and hence reclustering and reconfiguration of the system is often unavoidable. However, it is important to keep the topology stable as long as possible. The clustering algorithm can cooperate with routing algorithm in order to find routes between two nodes. This work mainly consist of three phases. The first phase consist of cleansing the network, which includes identifying the malicious nodes. The second phase consist of the weighted clustering of the network which incorporates a new reclustering condition known as stability factor. The third phase consist of a fuzzy method to choose the best path among the paths available for routing based on the residual energy and mobility of the nodes in the paths.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122303983","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: 8

A review on image processing and image segmentation 图像处理与图像分割的研究进展

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684170

Jiss Kuruvilla, D. Sukumaran, Anjali Sankar, S. P. Joy

引用次数: 73

Multiobjective linear programming model having fuzzy random variables following joint extreme value distribution 具有模糊随机变量服从联合极值分布的多目标线性规划模型

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684155

A. Biswas, A. K. De

{"title":"Multiobjective linear programming model having fuzzy random variables following joint extreme value distribution","authors":"A. Biswas, A. K. De","doi":"10.1109/SAPIENCE.2016.7684155","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684155","url":null,"abstract":"This paper presents a new technique for solving fuzzy multiobjective chance constrained programming problems in which the right sided parameters associated with the system constraints follow joint extreme value distribution. At first the multiobjective fuzzy stochastic model is converted into an equivalent fuzzy programming model applying chance constrained programming methodology and using the properties ofα - cuts. Then using the method of defuzzification of fuzzy numbers the fuzzy programming model is converted into a comparable deterministic model. Afterwards, solving each objective independently, the imprecise aspiration level to each of the individual objectives are obtained. Then the membership function for each objective is defined to measure the degree of achievements of the goal levels of the objectives. Finally, weighted fuzzy goal programming technique is applied to achieve the highest degree of each of the defined membership goals to the extent possible by minimizing under deviational variables of the fuzzy goals in the fuzzy stochastic decision making context. To illustrate the proposed approach, a numerical example is considered and solved.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121269393","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

Attribute selection and Customer Churn Prediction in telecom industry 电信行业属性选择与客户流失预测

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684171

V. Umayaparvathi, K. Iyakutti

引用次数: 24

Novel multi-server authentication protocol using secret sharing 基于秘密共享的新型多服务器认证协议

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684135

K. Nimmy

引用次数: 4

Electronic commerce process as a method to improve the product and process 电子商务过程作为一种改进产品和过程的方法

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684126

P. Dijesh, S. Babu

引用次数: 0

Document classification with a weighted frequency pattern tree algorithm 基于加权频率模式树算法的文档分类

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684140

Froila Helixia Dsouza, V. S. Ananthanarayana

{"title":"Document classification with a weighted frequency pattern tree algorithm","authors":"Froila Helixia Dsouza, V. S. Ananthanarayana","doi":"10.1109/SAPIENCE.2016.7684140","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684140","url":null,"abstract":"Document classification can be defined as the task of automatically categorizing collections of electronic documents into their annotated classes, based on their contents. It is an important problem in Data mining. Due to the exponential growth of documents in the Internet and the emergent need to organize them, developing an efficient document classification method to automatically manipulate web documents is of great importance and has received an ever-increased attention in the recent years. However, the existing approaches to text classification treat documents primarily as a bag of words, where all the information about the document is gathered based on the presence of individual words in the document, and not in what order or context those words appear in a sentence. In this paper we investigate the possibility of adopting the FP-tree, a data structure used in itemset mining, for the representation of training documents in text classification while preserving sentence information. Comparison between our method and other conventional document classification algorithms is conducted on several corpora. The experimental results indicate that our proposed algorithm yields much better performance than other conventional algorithms, especially the ones with primarily disjoint classification categories.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114766598","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

Book Recommendation System through content based and collaborative filtering method 图书推荐系统采用基于内容和协同过滤的方法

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684166

Praveen Mathew, B. Kuriakose, V. Hegde

{"title":"Book Recommendation System through content based and collaborative filtering method","authors":"Praveen Mathew, B. Kuriakose, V. Hegde","doi":"10.1109/SAPIENCE.2016.7684166","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684166","url":null,"abstract":"The online recommendation system has become a trend. Now a days rather than going out and buying items for themselves, reason being, online recommendation provides an easier and quicker way to buy items and transactions are also quick when it is done online. Recommended systems are powerful new technology and it helps users to find items which they want to buy. A recommendation system is broadly used to recommend products to the end users that are most appropriate. Online book selling Web sites now-a-days is competing with each other by considering many attributes. A recommendation system is one of the strongest tools to increase profits and retaining buyer. The existing systems lead to extraction of irrelevant information and lead to lack of user satisfaction. This paper presents Book Recommendation System (BRS) based on combined features of content based filtering (CBF), collaborative filtering (CF) and association rule mining to produce efficient and effective recommendation. For this we are proposing a hybrid algorithm in which we combine two or more algorithms, so it helps the recommendation system to recommend the book based on the buyer's interest.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133331516","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: 64