Augmenting SCA project management and automation framework

Iyapparaja, M.; Sharma, Bhanupriya

doi:10.1088/1757-899x/263/4/042018

Cited by 14 publications

(14 citation statements)

References 1 publication

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“…What"s more, collected score encourage to change-point investigation or with burst recognition, at last demonstrate that to distinguish emerging themes proper in light of the specify in everyday community share. Our strategy is to gather number of genuine information from ongoing twitter account [7].…”

Section: Litreature Surveymentioning

confidence: 99%

Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks

Manivannan*,

Iyapparaja,

Prasanna

et al. 2019

IJRTE

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Social network is a place where people exchange and share data related to the current trends and events all over the world. This specific behavior of users made us concentrate on the logic that processing these data may lead us to the extracting the current topic of curiosity between the users. Applying data clustering technique likeTerm-document-Frequency (TDF) based approach over these data may leads us up to the mark but there will be little chance of negatives. We are going to do a likely medium that can give both usual mentioning behaviour of a consumer and also the frequency of users occurring in their mentions. It also works well even the data of the messages are very small information. These extracted emerging topic are shown to the user those who subscribe for the details.

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Section: Litreature Surveymentioning

confidence: 99%

Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks

Manivannan*,

Iyapparaja,

Prasanna

et al. 2019

IJRTE

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“…The results obtained by this technique is SVM has 82.55% and KNN with 78,81%. N. SenthilMurugan and G. Usha Devi [20][21][22][23] have proposed hybrid techniques using machine learning approaches with optimization techniques and reviewed the concept and uses of other approaches and compared the results for their classification.…”

Section: Related Workmentioning

confidence: 99%

A Detailed Research on Detection of Polycystic Ovary Syndrome from Ultrasound Images of Ovaries

2019

IJRTE

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A common endocrine disorder named polycystic ovarian syndrome (PCOS) usually occurs to several women’s during their reproductive age. This type of disease leads to infertility which represent with amenorrhea and hirsutism. The combination of clinical, endocrinological, and biochemical abnormalities are known to be PCOS which particularly related with the metabolism of estrogen and androgens. The periphery of ovaries is identified with the most common immature follicles which are less than 10mm. Analyzing this kind of situations in women is a major challenge which now doctors used ultrasound images which have the necessary details like number of follicles, size, and position. For real-time analysis of PCOS is a major task as follicles contains different sizes and highly connected with tissues and blood vessels which results in error prone. Several researchers have proposed different techniques for analyzing the PCOS using the ultrasound images of ovaries. In this study, we analyze the important factors and techniques used in detection of PCOS by using the ultrasound images taken from the women’s ovary and compared the results of existing works.

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“…Text classification is a process of categorizing text data into groups by using Natural Language Processing (NLP) [14], [15].…”

Section: Text Classificationmentioning

confidence: 99%

Diminishing Spread of False Message in Twitter using Block chain and Machine Learning

2019

IJEAT

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A communication platform such as social media often works to change or influence opinions when it comes to political views. Microblogging platforms such as Facebook, Pinterest, Tumblr, Instagram enable users to con- tribute new postings which are publicly visible. Twitter stood out as overpowering news equipment, giving information to the world. It is very common for users to logo on to this site for immediate update on recent happenings like natural disasters, political events etc. Due to the enlarging reputation of Twitter, this aroused spammers to circulate false information. The proposed scheme seeks to reduce the spread of false information in Twitter using blockchain consensus algorithm, along with classification and machine learning algorithms. A "tweet" gets posted based on the validation provided by the nodes in the blockchain. The system works according to the sensitivity of the tweet.

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Augmenting SCA project management and automation framework

Cited by 14 publications

References 1 publication

Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks

Term Document Frequency (TDF) Method for Extracting User Posts and Emerging Events in Social Networks

A Detailed Research on Detection of Polycystic Ovary Syndrome from Ultrasound Images of Ovaries

Diminishing Spread of False Message in Twitter using Block chain and Machine Learning

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