2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)最新文献

GP-GPU based high-performance test equipment for debugging radar digital units 基于GP-GPU的高性能雷达数字单元调试测试设备

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684173

R. Badarinath, M. Abhilash

引用次数: 0

An efficient video Steganography technique for secured data transmission 一种用于安全数据传输的高效视频隐写技术

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684125

Dhanya Job, V. Paul

引用次数: 5

Multi-document text summarization - a survey 多文档文本摘要-一项调查

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684115

A. Tandel, Brijesh Modi, Priyasha Gupta, Shreya Wagle, Sujata Khedkar

引用次数: 11

Prediction of election result by enhanced sentiment analysis on twitter data using classifier ensemble Approach 基于分类器集成的twitter数据增强情感分析预测选举结果

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684133

R. Jose, Varghese S. Chooralil

{"title":"Prediction of election result by enhanced sentiment analysis on twitter data using classifier ensemble Approach","authors":"R. Jose, Varghese S. Chooralil","doi":"10.1109/SAPIENCE.2016.7684133","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684133","url":null,"abstract":"Sentiment analysis is the computational study of opinions, sentiments, evaluations, attitudes, views and emotions expressed in text. It refers to a classification problem where the main focus is to predict the polarity of words and then classify them into positive or negative sentiment. Sentiment analysis over Twitter offers people a fast and effective way to measure the public's feelings towards their party and politicians. The primary issue in previous sentiment analysis techniques is the determination of the most appropriate classifier for a given classification problem. If one classifier is chosen from the available classifiers, then there is no surety in the best performance on unseen data. So to reduce the risk of selecting an inappropriate classifier, we are combining the outputs of a set of classifiers. Thus in this paper, we use an approach that automatically classifies the sentiment of tweets by combining machine learning classifiers with lexicon based classifier. The new combination of classifiers are SentiWordNet classifier, naive bayes classifier and hidden markov model classifier. Here positivity or negativity of each tweet is determined by using the majority voting principle on the result of these three classifiers. Thus we were used this sentiment classifier for finding political sentiment from real time tweets. Thus we have got an improved accuracy in sentiment analysis using classifier ensemble Approach. Our method also uses negation handling and word sense disambiguation to achieve high accuracy.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125537308","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: 51

Application of Data Mining in Higher Secondary Directorate of Kerala 数据挖掘在喀拉拉邦高等中学理事会的应用

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684139

S. Mathew, John T. Abraham

引用次数: 1

Accelerometer based human activities and posture recognition 基于人类活动和姿势识别的加速度计

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684120

A. Babu, Kudakwashe Dube, S. Mukhopadhyay, H. Ghayvat, Kumar M. V. Jithin

引用次数: 9

An effective communication framework for data management using query caching in Mobile Location based Services (LBS) 基于移动位置服务(LBS)的查询缓存数据管理的有效通信框架

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684119

R. Gobi, E. Kirubakaran

{"title":"An effective communication framework for data management using query caching in Mobile Location based Services (LBS)","authors":"R. Gobi, E. Kirubakaran","doi":"10.1109/SAPIENCE.2016.7684119","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684119","url":null,"abstract":"Technology has transformed the mobile phone as a big medium for communication and offered a pool of services to the subscriber. Among those services, Location Based Services (LBS) is prominent to get services based on current geographic location. The services include right from information to entertainment and the services offered by LBS are highly dynamic because its access pattern is different from one location to another location. It directly deals with positioning the location and providing the information. Since it deals with dynamic and real time, conventional data handling techniques may not suitable and there are several issues like increased communication cost, increased query processing time, in-ability of accurate positioning needs to be addressed to utilize the full benefit of LBS. Hence this research work focuses on providing solution for data management issues. Based on classification of applications and categorization of services in LBS, a communication framework (ComFrame) with several layers is proposed. The framework applies a data management technique called q-caching to store user's frequent queries in Cache Manager (Local Manager), and this approach has been implemented in both on client and server side with Android API and Java Remote Method Invocation (RMI) services. The proposed scheme results in reduced communication cost, query handling time and data volume by applying Cost Benefit Analysis techniques. In summary, dynamic data management principles enhances Mobile Location based Services. This framework can further be enhanced to Governance and Business sectors for effective utilization of mobile data management in future.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127266562","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

A study on Down syndrome detection based on Artificial Neural Network in Ultra sonogram images 基于人工神经网络的超声像图唐氏综合征检测研究

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684172

Devi V. K. Vincy, R. Rajesh

{"title":"A study on Down syndrome detection based on Artificial Neural Network in Ultra sonogram images","authors":"Devi V. K. Vincy, R. Rajesh","doi":"10.1109/SAPIENCE.2016.7684172","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684172","url":null,"abstract":"Down syndrome is a genetic disorder in which disrupts infants, physical and cognitive development. Down syndrome is characterized by the absence of nasal bone during the late first trimester of pregnancy. Presently Down syndrome is identified by visually examining the ultra sonogram image of foetus of 11 to 13 weeks of gestation for the presence of nasal bone. The visually identification by the change in the contrast of nasal bone region of ultra sonogram is a very difficult task. So the image processing based features extraction by considering various parameters have been extremely important. This paper provides comprehensive survey on various medical imaging techniques that can be effectively used for detecting the syndrome in the early stage of pregnancy. Our proposed survey consider different methods based on the various parameters extracted using a series of operations such as Region Of Interest (ROI), Nasal Bone (NB) segmentation using morphological, Otsu thresholding and logical operations from the ultra sonogram images, both in spatial domain as well as transform domain using Discrete Cosine Transform (DCT) and wavelet transforms. The extracted data is normalized and used to train classifiers like Back Propagation Neural Network (BPNN). This paper illustrates overview of various states of methods available in the Down syndrome detection and comparison analysis of each method is discussed.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132887068","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

Methods to detect different types of outliers 检测不同类型异常值的方法

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684114

D. Divya, S. Babu

引用次数: 10

Modified autonomy oriented computing based network immunization by considering betweenness centrality 考虑中间中心性的改进自主计算网络免疫

2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-16 DOI: 10.1109/SAPIENCE.2016.7684128

Susan K. Paul, Biju Abraham Narayamparambil

{"title":"Modified autonomy oriented computing based network immunization by considering betweenness centrality","authors":"Susan K. Paul, Biju Abraham Narayamparambil","doi":"10.1109/SAPIENCE.2016.7684128","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684128","url":null,"abstract":"As many people rely on Internet and mobile phone for many applications, it is very crucial for society. Networks, formed by the connection of devices following some relationships among users, provide good platforms for virus spread. Viruses can cause data leakage and can even jam wireless services by sending thousands of Spam messages, and reduce the quality of voice communication. In order to protect devices from virus attack several immunization methods are used, where some nodes in a network are immunized so that they cannot be infected by a virus. Due to high cost of immunization, the main aim of immunization becomes how to immunize a small or minimum number of important nodes in order to prevent a virus from spreading to major parts of the network. Most of the immunization methods are executed in centralized and static networks but in actual situation computer networks are decentralized, dynamic and scalable in nature. In the method discussed here some entities are deployed into the network, these entities interact with each other to locate highly connected nodes. The goal of this work is to implement modified AOC based immunization by considering betweenness centrality and analyze its results on different network topology.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115384963","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