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Title: :  Data Mining and Social Web Semantics
PaperId: :  10113
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 5 Issue 2 2019
DUI:    16.0415/IJARIIE-10113
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
sonali panchbhaiSRM Institute of Science and Technology
Atul AnandSRM Institute of Science and Technology
Khushi SurekaSRM Institute of Science and Technology
Ms. S. AbinayaaSRM Institute of Science and Technology

Abstract

Information Technology
Data Mining , Social web, hashtags , data , twitter, comments, sentiments analysis, positive , negative
Hashtags, initially presented in Twitter, are currently turning into the most utilized approach to label short messages in informal organizations since this encourages ensuing pursuit, characterization and bunching over those messages. In any case, separating data from hashtags is troublesome on the grounds that their creation isn't compelled by any (phonetic) standard and they normally show up in short and ineffectively composed messages which are hard to break down with exemplary IR procedures. In this task we address two testing issues with respect to the "significance of hashtags"— in particular, hashtag relatedness and hashtag characterization — and we give two principle commitments. First we manufacture a novel diagram upon hashtags and (Wikipedia) elements drawn from the tweets by methods for subject annotators, (for example, TagME); this chart will enable us to show in a solid way great co-events as well as semantic relatedness among hashtags and elements, or between substances themselves. In light of this diagram, we plan calculations that fundamentally improve best in class results upon known freely accessible datasets. The second commitment is the development and the open discharge to the examination network of two new datasets: the previous is another dataset for hashtag relatedness, the last is a dataset for hashtag characterization that is up to two requests of greatness bigger than the current ones. These datasets will be utilized to demonstrate the power and adequacy of our methodologies, appearing in F1 up to two-digits in rate (outright).

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IJARIIE sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. "Data Mining and Social Web Semantics" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 2 2019 Page 2776-2782
MLA sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. "Data Mining and Social Web Semantics." International Journal Of Advance Research And Innovative Ideas In Education 5.2(2019) : 2776-2782.
APA sonali panchbhai, Atul Anand, Khushi Sureka, & Ms. S. Abinayaa. (2019). Data Mining and Social Web Semantics. International Journal Of Advance Research And Innovative Ideas In Education, 5(2), 2776-2782.
Chicago sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. "Data Mining and Social Web Semantics." International Journal Of Advance Research And Innovative Ideas In Education 5, no. 2 (2019) : 2776-2782.
Oxford sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. 'Data Mining and Social Web Semantics', International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, 2019, p. 2776-2782. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Data_Mining_and_Social_Web_Semantics_ijariie10113.pdf (Accessed : ).
Harvard sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. (2019) 'Data Mining and Social Web Semantics', International Journal Of Advance Research And Innovative Ideas In Education, 5(2), pp. 2776-2782IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Data_Mining_and_Social_Web_Semantics_ijariie10113.pdf (Accessed : )
IEEE sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa, "Data Mining and Social Web Semantics," International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, pp. 2776-2782, Mar-App 2019. [Online]. Available: https://ijariie.com/AdminUploadPdf/Data_Mining_and_Social_Web_Semantics_ijariie10113.pdf [Accessed : ].
Turabian sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. "Data Mining and Social Web Semantics." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 5 number 2 ().
Vancouver sonali panchbhai, Atul Anand, Khushi Sureka, and Ms. S. Abinayaa. Data Mining and Social Web Semantics. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2019 [Cited : ]; 5(2) : 2776-2782. Available from: https://ijariie.com/AdminUploadPdf/Data_Mining_and_Social_Web_Semantics_ijariie10113.pdf
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