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Int. J. Rough Sets Data Anal.最新文献

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Tradeoffs Between Forensics and Anti-Forensics of Digital Images 数字图像取证与反取证的权衡
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040107
P. Shelke, R. Prasad
{"title":"Tradeoffs Between Forensics and Anti-Forensics of Digital Images","authors":"P. Shelke, R. Prasad","doi":"10.4018/IJRSDA.2017040107","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040107","url":null,"abstract":"Over past few years, we are the spectators of the evolution in the field of information technology, telecommunication and networking. Due to the advancement of smart phones, easy and inexpensive access to the internet and popularity of social networking, capture and use of digital images has increased drastically. Image processing techniques are getting developed at rapidly and at the same time easy to use image tampering soft-wares are also getting readily available. If tampered images are misused, big troubles having deep moral, ethical and lawful allegations may arise. Due to high potential of visual media and the ease in their capture, distribution and storage, we rarely find a field where digital visual data is not used. The value of image as evidence of event must be carefully assessed and it is a call for from different fields of applications. Therefore, in this age of fantasy, image authentication has become an issue of utmost importance.","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132311408","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: 11
Twitter Intention Classification Using Bayes Approach for Cricket Test Match Played Between India and South Africa 2015 使用贝叶斯方法对2015年印度和南非板球测试赛进行Twitter意图分类
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040104
V. D. Jadhav, S. Deshmukh
{"title":"Twitter Intention Classification Using Bayes Approach for Cricket Test Match Played Between India and South Africa 2015","authors":"V. D. Jadhav, S. Deshmukh","doi":"10.4018/IJRSDA.2017040104","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040104","url":null,"abstract":"Information retrieval and forecasting in real time is becoming the fastest and most efficient way to obtain useful knowledge of what is happening now, allowing organizations to react quickly when problem appears which help to improve their performance. There is enormous amount of data in the form of tweets. It builds data processing system that creates informative data about the cricket test matches. Using twitter data, the authors find the sentiments or polarity of fans posting tweets related to game. Polarity is given as positive, negative and neutral. The authors also analyze the feelings or emotions of people posting tweets. Emotions are given as anger, disgust, fear, joy, sadness, surprise and unknown. Machine learning algorithm (Bayes) using R technology shows the accuracy when trained with emotion data. KeywoRDS API, Bayes, Cricket, Emotions, Intention, MAE, Polarity, Sentiments, Tweets, Twitter","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114260333","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: 26
Survey on Privacy Preserving Association Rule Data Mining 隐私保护关联规则数据挖掘研究综述
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040105
G. Navale, S. Mali
{"title":"Survey on Privacy Preserving Association Rule Data Mining","authors":"G. Navale, S. Mali","doi":"10.4018/IJRSDA.2017040105","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040105","url":null,"abstract":"The progress in the development of data mining techniques achieved in the recent years is gigantic. The collative data mining techniques makes the privacy preserving an important issue. The ultimate aim of the privacy preserving data mining is to extract relevant information from large amount of data base while protecting the sensitive information. The togetherness in the information retrieval with privacy and data quality is crucial. A detailed survey of the present methodologies for the association rule data mining and a review of the state of art method for privacy preserving association rule mining is presented in this paper. An analysis is provided based on the association rule mining algorithm techniques, objective measures, performance metrics and results achieved. The metrics and the short comings of the various existing technologies are also analysed. Finally, the authors present various research issues which can be useful for the researchers to accomplish further research on the privacy preserving association rule data mining.","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128230928","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: 21
Mobile Sink with Mobile Agents: Effective Mobility Scheme for Wireless Sensor Network 带移动代理的移动Sink:无线传感器网络的有效移动方案
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040102
Rachana Borawake-Satao, R. Prasad
{"title":"Mobile Sink with Mobile Agents: Effective Mobility Scheme for Wireless Sensor Network","authors":"Rachana Borawake-Satao, R. Prasad","doi":"10.4018/IJRSDA.2017040102","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040102","url":null,"abstract":"Wireless Sensor Networks (WSN) has been drawing considerable attention and discussion in recent years due to its potential applications in various fields. In modern applications for future internet the MSN (Mobile Sensor Network) is a key factor. Mobility allows the applications of Wireless Sensor Network to be compatible with IoT (Internet of Things) applications. As mobility enhances capability of the network it also affects the performance of the network at each layer. In recent years the various methodologies are proposed to handle mobility. Most of them use mobility for efficient data collection in WSNs. The purpose of this paper is to study effects of mobility on various performance parameters of the network and to explore the effective techniques to handle mobility in network. This paper proposes Mobile Sink with Mobile Agent mobility model for WSN which will increase the lifetime of the network using sink and agent node mobility. KEyWoRDS Internet of Things (IoT), Mobile Sensor Network (MSN), Mobility, Wireless Sensor Network (WSN)","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125540815","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: 25
Stock Price Trend Prediction and Recommendation using Cognitive Process 基于认知过程的股价趋势预测与推荐
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040103
V. Bag, U. Kulkarni
{"title":"Stock Price Trend Prediction and Recommendation using Cognitive Process","authors":"V. Bag, U. Kulkarni","doi":"10.4018/IJRSDA.2017040103","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040103","url":null,"abstract":"","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115750534","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: 22
Medco: An Emergency Tele-Medicine System for Ambulance Medco:救护车紧急远程医疗系统
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040101
A. Saikar, Aditya Badve, M. Parulekar, Ishan Patil, S. Belsare, A. Deshmukh
{"title":"Medco: An Emergency Tele-Medicine System for Ambulance","authors":"A. Saikar, Aditya Badve, M. Parulekar, Ishan Patil, S. Belsare, A. Deshmukh","doi":"10.4018/IJRSDA.2017040101","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040101","url":null,"abstract":"","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123888123","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: 33
A Systematic Review on Author Identification Methods 作者鉴定方法系统综述
Int. J. Rough Sets Data Anal. Pub Date : 2017-04-01 DOI: 10.4018/IJRSDA.2017040106
S. Kale, R. Prasad
{"title":"A Systematic Review on Author Identification Methods","authors":"S. Kale, R. Prasad","doi":"10.4018/IJRSDA.2017040106","DOIUrl":"https://doi.org/10.4018/IJRSDA.2017040106","url":null,"abstract":"Author Identification is a technique for identifying author of anonymous text. It has near about 130 year’s long history, started with the work by Mendenhall 1987. Applications of Author identification include plagiarism detection, detecting anonymous author, in forensics and so on. In this paper the authors outline features used for Author identification like vocabulary, syntactic and others. Researchers worked on various methods for Author identification they also outline this paper on types of Author Identification methods that include 1. Profile-based Approaches which includes Probabilistic Models, Compression Models, Common n-Grams (CNG) approach, 2. Instance-based Approaches which includes Vector Space Models, Similarity-based Models, Meta-learning Models and 3. Hybrid Approaches. At the end the authors conclude this paper with observations and future scope. KeywoRDS Attribution Method, Author Identification, Feature Set, Text Features, Text Mining","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124534439","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: 9
Discovering Patterns using Process Mining 使用过程挖掘发现模式
Int. J. Rough Sets Data Anal. Pub Date : 2016-10-01 DOI: 10.4018/IJRSDA.2016100102
Ishak H. A. Meddah, K. Belkadi
{"title":"Discovering Patterns using Process Mining","authors":"Ishak H. A. Meddah, K. Belkadi","doi":"10.4018/IJRSDA.2016100102","DOIUrl":"https://doi.org/10.4018/IJRSDA.2016100102","url":null,"abstract":"Process mining provides an important bridge between data mining and business process analysis, his techniques allow for extracting information from event logs. In general, there are two steps in process mining, correlation definition or discovery and then process inference or composition. Firstly, the authors' work consists to mine small patterns from a log traces of two applications; SKYPE, and VIBER, those patterns are the representation of the execution traces of a business process. In this step, the authors use existing techniques; The patterns are represented by finite state automaton or their regular expression; The final model is the combination of only two types of small patterns whom are represented by the regular expressions ab* and ab*c*. Secondly, the authors compute these patterns in parallel, and then combine those small patterns using the composition rules, they have two parties the first is the mine, they discover patterns from execution traces and the second is the combination of these small patterns. The patterns mining and the composition is illustrated by the automaton existing techniques. The Execution traces are the different actions effected by users in the SKYPE and VIBER. The results are general and precise. It minimizes the execution time and the loss of information.","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125324056","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: 27
An Approach to Distinguish Between the Severity of Bullying in Messages in Social Media 一种区分社交媒体信息中欺凌严重性的方法
Int. J. Rough Sets Data Anal. Pub Date : 2016-10-01 DOI: 10.4018/IJRSDA.2016100101
Geetika Sarna, M. Bhatia
{"title":"An Approach to Distinguish Between the Severity of Bullying in Messages in Social Media","authors":"Geetika Sarna, M. Bhatia","doi":"10.4018/IJRSDA.2016100101","DOIUrl":"https://doi.org/10.4018/IJRSDA.2016100101","url":null,"abstract":"Users on the social media can share positive as well as negative information intentionally and unintentionally in the form of multimedia content without knowing its impact on other user, which threatens the security and privacy of social media. Cyberbullying is one of the risks associated with social media. Cyberbullying is an aggressive act carried out intentionally against the victim by posting harmful material on social media to harm his/her reputation. Aggressive act creates depression, anxiety in users which may lead to diversion of attention and sometimes suicidal actions. In this paper the authors have included a survey on recent algorithms which work on detection of cyberbullying. State-of-the-art studies only focus on the detection of cyberbullying but not on the preventive measures against cyberbullying. In order to tackle this problem, the authors showed how the severity of the bullying in messages helps to find the real culprit.","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124112518","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: 23
Classification of Polarity of Opinions Using Unsupervised Approach in Tourism Domain 基于无监督方法的旅游领域意见极性分类
Int. J. Rough Sets Data Anal. Pub Date : 2016-10-01 DOI: 10.4018/IJRSDA.2016100105
Mahima Goyal, Vishal Bhatnagar
{"title":"Classification of Polarity of Opinions Using Unsupervised Approach in Tourism Domain","authors":"Mahima Goyal, Vishal Bhatnagar","doi":"10.4018/IJRSDA.2016100105","DOIUrl":"https://doi.org/10.4018/IJRSDA.2016100105","url":null,"abstract":"The recent growth of e-commerce websites has paved a way for the users to express their opinions on these web portals which, in turn, makes the customers review these comments before buying any product or service. The comprehensive reading of these large number of reviews is cumbersome and tiring. The purpose of this paper is to perform the analysis on the tourism domain reviews to decide whether the document is positive or negative. The traditional methods use a machine learning approach, but the authors are using an unsupervised dictionary based approach to classify the opinions. The scores of the opinions are extracted using Sentiwordnet, a popular dictionary for calculating the sentiment.","PeriodicalId":152357,"journal":{"name":"Int. J. Rough Sets Data Anal.","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122476525","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: 37
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