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Deepika, S.
- Enriched Server and Client Side Based Personalized Secure Web Search
Abstract Views :184 |
PDF Views:3
Authors
Affiliations
1 Department of IT, KSR College of Engineering, Tamilnadu, IN
1 Department of IT, KSR College of Engineering, Tamilnadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 1, No 2 (2015), Pagination: 1-5Abstract
As the size of the Internet continues to grow the users of search providers continually demand search results that are accurate to their needs. Personalized Search is one of the options available to users in order to sculpt search results returned to them based on their personal data provided to the search provider. This raises concerns of privacy issues however as users are typically uncomfortable revealing personal information to an often faceless service provider on the Internet. This paper aims to deal with the privacy issues surrounding personalized search and discusses ways that privacy can be enriched by using encryption on user's information, so that users can become more comfortable with the release of their personal data in order to receive more accurate search results.Keywords
Personalized Search, Privacy Issues, Encryption.- Anonymity,Unlinkability,Unobservability for Routing Protocol in MANETs
Abstract Views :249 |
PDF Views:2
Authors
Affiliations
1 Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, Tamilnadu, IN
1 Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, Tamilnadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 1, No 1 (2014), Pagination: 1-5Abstract
Privacy protection of mobile ad hoc networks is more demanding than that of wired networks due to the open nature and mobility of wireless media. In wired networks, one has to gain access to wired cables so as to eavesdrop communications. Privacy-preserving routing is crucial for some ad hoc networks that require stronger privacy protection. In hostile environments, the enemy can launch traffic analysis against interceptable routing information embedded in routing messages and data packets. Allowing adversaries to trace network routes and infer the motion pattern of nodes at the end of those routes may pose a serious threat to covert operations. A number of schemes have been proposed to protect privacy in ad hoc networks. However, none of these schemes offer complete unlink ability or unobservability property since data packets and control packets are still linkable and distinguishable in these schemes. In this paper, we define stronger privacy requirements regarding privacypreserving routing in mobile ad hoc networks. Anonymous key establishment process and route discovery process authenticates the routing paths taken by individual messages. Achieving anonymity is a different problem than achieving data confidentiality. While data can be protected by cryptographic means, the recipient node address and maybe the sender node address of a packet cannot be simply encrypted because they are needed by the network to route the packet.Keywords
Mobile Ad Hoc Networks, Anonymity, Routing Protocol, Geographical Routing.- Predicting Polarity Using Sentimental Analysis
Abstract Views :261 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 6, No 1 (2020), Pagination: 01-04Abstract
Sentiment analysis is a study of people’s sentiments, opinions, attitudes, emotions in a written language or text. Rapid Growth in the field of sentiment analysis and explore to find the sentiment on various social media platforms using techniques of machine learning with analyzing sentiment, and also helps in the analysis of polarity or subjectivity. The most widely used social media site is Twitter, where people share their thoughts in the form of tweets and hence it becomes the major data sources of sentimental analysis. Recently the more used social media platform such as Twitter. Their people express their thoughts and opinion as a tweet representation. It is the major data resources of analyzing the sentiments. Sentiments are classified to different group like positive, negative or neutral. Such analysis process helps to differentiate the sentiments also classifying them into different groups comes under prediction of sentiment. Very first we pre-process the dataset, feature extraction in which meaningful insights are extracted from the dataset, then extracted features are applied for classification model using machine learning Random Forest algorithm, Regression algorithm, etc. But with the advancement of the python language and to reduce the code complexity we have analyzed the polarity using the python packages, API and Algorithm which are available. This model proved to be highly effective and accurate on the analysis of feelings. At last the trained classification model are tested in order to check the performance it is measured by accuracy.Keywords
Classification, Random forest, Regression, Sentimental analysis.References
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