Recommendation of online Products Using Microblogging Information in Social Media
K. Srinivas1, V Shivanarayana Reddy2, B Ramya3
1Dr. K, Srinivas, Department of CSE, Geethanjali College of Engineering and Technology, Hyderabad, India.
2V Shivanarayana Reddy, Department of CSE, Geethanjali College of Engineering and Technology, Hyderabad, India.
3B Ramya, Department of CSE, Geethanjali College of Engineering and Technology, Hyderabad, India.
Manuscript received on 04 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 473-477 | Volume-8 Issue-10, August 2019 | Retrieval Number: I8524078919/2019©BEIESP | DOI: 10.35940/ijitee.I8524.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: (Please read carefully abstract of the template). With the usage of social network like Facebook or Twitter sign-in’s as e-commerce sign-in where user are enabled to post on micro blogs linking to the e-commerce webpages, this mechanism has weakened the restrictions between e-commerce and social networking. A process of referring products to users of social networking by E-commerce sites in Cold-Start situations which is very rare is proposed where the question for knowledge isolation becomes the issue. This problem can be overcome by linking social networking and E-commerce pages as a bridge using features signs and information from neural networks adopting an improved ascent helping Tree method to move social networking users as user embedding’s. This can be done by employing a matrix factorization and trial done on Chinese micro-blogging service SINA WEIBO and Chinese B2C E-commerce website JINGDONG show that the proposed method is efficient.
Keywords: E-commerce, Social media, OSN, SINA WEIBO, ColdE, CBOW.
Scope of the Article: E-governance, E-Commerce, E-business, E-Learning