A Framework to Collect and Visualize User’s Browser History for Better User Experience and Personalized Recommendations

Kandala, Harish; Tripathy, B. K.; Kumar, K. Suresh

doi:10.1007/978-3-319-63673-3_26

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…At long last, they built up a corpus-technique to build a pseudo-antonym lexicon. Researchers of the paper [3] focused on designing understudies' Twitter presents on get issues and glitches in their instructive encounters. They previously directed a subjective investigation on tests engaged from around 25K tweets associated to designing understudies' school life.…”

Section: Methodlogies Of Sentiment Analysismentioning

confidence: 99%

Enhanced Text Mining Methodology in Social Media Platform

Kumar*¹,

Sandeep²,

Kumar³

et al. 2019

IJITEE

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For past few years, the World Wide Web has turned into an immense wellspring of client produced content and opinionative information. Utilizing web-based life, for example, Instagram, Facebook, twitter, etc., users share their views and feelings in an advantageous manner. Web-based social networking, for example, Instagram, Facebook, twitter, etc., where a huge number of individuals prompt their individual perspectives in their everyday communication, which may be their assumptions & sentiments about specific thing. These consistently developing emotional information are, without a doubt, an incredibly rich wellspring of data for any sort of basic leadership method. To computerize examination of such information, region of Sentiment Analysis has been developed. It goes for recognizing opinionative information in the Web & characterizing it as indicated by their polarities., regardless of whether they convey a positive/negative implication. Assessment Study is an issue of content-based examination, yet there are a few difficulties that make it troublesome when contrasted with conventional content-based investigation This unmistakably expresses there is need of an endeavor to move in the direction of these issues and it has opened up a few open doors for future research for taking care of refutations, concealed assumptions ID, slangs, polysemy. Be that as it may, the developing size of information requests programmed information examination strategies. In this paper, a literature review on various strategies utilized in the Sentiment Analysis is done to comprehend dimension of the work

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Section: Methodlogies Of Sentiment Analysismentioning

confidence: 99%

Enhanced Text Mining Methodology in Social Media Platform

Kumar*¹,

Sandeep²,

Kumar³

et al. 2019

IJITEE

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show abstract

“…After the fixing motor parts of the bargains, security assessment model at that point gives out one new score, as indicated by the fixed outcomes [14]. Usage of our computable secure assessment framework has been done dependent on our G Cloud Platform [15]. Our exploratory stage contains 2 free Clouds.…”

Section: Repair Security Vulnerabilitymentioning

confidence: 99%

Security Validation Model in Cloud Computing Environment

Goswami¹,

Diwedi²

2020

IJEAT

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Private, Public cloud or a unified cloud system, client’s absence of a successful secure computable assessment techniques for handling the security circumstance of its own data foundation overall. This paper gives a quantifiable security assessment framework for various mists that can be gotten to by reliable API. The assessment framework incorporates security checking motor, security recuperation motor, secure computable assessment system, graphical presentation segment & so on. Secure assessment system makes out of many assessment components comparing various fields, for example, figuring, stockpiling, organize, support, application security and so forth. Every component is doled out 3 tuples on the liabilities, score & fix strategy. Framework receives "1 vote" system for a field to check its point & includes synopsis as overall score, & to make high security. We implement the computable assessment for various cloud environment clients dependent on the G Cloud phase. It displays active security examining for one or different clouds with pictorial diagrams & clients to adjust arrangement, expand activity & fix liabilities, in order to increase secureness of cloud assets.

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“…For over groups which have volatile correspondence Google uses portray it explicit for it. Be that as it may, in ML they built up a light weight draftsman [3] by multicores utilizing map-diminish strategies. In conventional way information is stacking into one stockroom; yet typically it is unimaginable on the grounds that we utilized information from various stages like insurance agency, labs and organizations, where all of them require specific information and all are not put away information which identified with them.…”

Section: Literature Workmentioning

confidence: 99%

Data Entities & its Privacy with Big Data Techniques in e-health systems

Khan,

Reddy,

Kumar*

2019

IJEAT

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Enormous information is rising innovation now in different territories, i.e. like online purchase, online medical services, tweet investigation, and saving money area. Presently today's insurance agencies are appearing towards investigation of their tremendous data samples comprises of patients & healing center's data. From those informational indexes they extricating some valuable data. For the most part they focus on progress and disappointment rate and input provided by the patients. Patients are going to provide the hospital center bills alongside release outline, medicinal reports to the insurance agency. In point of patient system assurance agency is choosing to endorse case & recommend for newly coming patients. In this paper, patient reports, indications, log records & criticisms are dissected utilizing enormous information innovations like infinispan and guide lessen ideas for information extraction and isolation in E-medical coverage. Uncovering of patient’s confidential data has been finished utilizing confidential information encrypting calculation.

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A Framework to Collect and Visualize User’s Browser History for Better User Experience and Personalized Recommendations

Cited by 11 publications

References 5 publications

Enhanced Text Mining Methodology in Social Media Platform

Enhanced Text Mining Methodology in Social Media Platform

Security Validation Model in Cloud Computing Environment

Data Entities & its Privacy with Big Data Techniques in e-health systems

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