SPDM in Social Media for the Development of Business
D. Gandhimathi1, A. John Sanjeev Kumar2
1D. Gandhimathi*, Research Scholar & Assistant Professor, Bharathiar University, Coimbatore. Thiagarajar College, Madurai, Tamil Nadu, India.
2Dr. A. John Sanjeev Kumar, Assistant Professor, the American College, Madurai, Tamil Nadu, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 26, 2020. | Manuscript published on March 10, 2020. | PP: 2088-2091 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2863039520/2020©BEIESP | DOI: 10.35940/ijitee.E2863.039520
Open Access | Ethics and Policies | Cite | Mendeley
© 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: In Modern era Social Media(SM) is a place of communication with collective information. Spatial Data Mining(SPDM) are acknowledged as mining of spatial knowledge among attractive pattern from various forms of Spatial Data. SPDM focus to theory and Methodology and process for extracting useful information through spatial data. Spatial Data are attributes of neighbors of selected object. SM and their role played in daily life increased considerably over the last few years. To examine collaboration among friends in a SM pattern of relationship is essential, for development of digitalized businesses in trading process. Data extracted with SPDM is utilized with KNG technique to identify the highly recommended product among clustered users. This paper illustrate the betterment of KNG while compared with KNN process using Spatial Data for the development of Business.
Keywords: Spatial Data Mining, Spatial Data , Social Media, KNG, KNN.
Scope of the Article: Data Mining