Web mediated crowd funding is a talented paradigm used by project launcher to solicit funds from backers to realize projects. Kickstarter is one such largest funding platform for creative projects. However, not all the campaigns in Kickstarter attain their funding goal and are successful. It is therefore important to know about campaigns’ chances of success. As a broad goal, authors intended in extraction of the hidden knowledge from the Kickstarter campaign database and classification of these projects based on their dependency parameters. For this authors have designed a classification model for the analysis of Kickstarter campaigns by using direct information retrieved from Kickstarter URLs. This aids to identify the possibility of success of a campaign.
%0 Journal Article
%1 conf/ifip13/ThengTT10a
%A "R. S, Kamath"
%A "R. K, Kamat"
%D 2016
%J International Journal of Information Technology, Modeling and Computing (IJITMC)
%K R classifiers crowd funding kickstarter learning machine prediction systems
%N 1
%P 12
%R 10.5121/ijitmc.2016.4102
%T SUPERVISED LEARNING MODEL FOR KICKSTARTER CAMPAIGNS WITH R MINING
%U http://aircconline.com/ijitmc/V4N1/4116ijitmc02.pdf
%V 4
%X Web mediated crowd funding is a talented paradigm used by project launcher to solicit funds from backers to realize projects. Kickstarter is one such largest funding platform for creative projects. However, not all the campaigns in Kickstarter attain their funding goal and are successful. It is therefore important to know about campaigns’ chances of success. As a broad goal, authors intended in extraction of the hidden knowledge from the Kickstarter campaign database and classification of these projects based on their dependency parameters. For this authors have designed a classification model for the analysis of Kickstarter campaigns by using direct information retrieved from Kickstarter URLs. This aids to identify the possibility of success of a campaign.
@article{conf/ifip13/ThengTT10a,
abstract = {Web mediated crowd funding is a talented paradigm used by project launcher to solicit funds from backers to realize projects. Kickstarter is one such largest funding platform for creative projects. However, not all the campaigns in Kickstarter attain their funding goal and are successful. It is therefore important to know about campaigns’ chances of success. As a broad goal, authors intended in extraction of the hidden knowledge from the Kickstarter campaign database and classification of these projects based on their dependency parameters. For this authors have designed a classification model for the analysis of Kickstarter campaigns by using direct information retrieved from Kickstarter URLs. This aids to identify the possibility of success of a campaign.
},
added-at = {2018-01-03T05:14:59.000+0100},
author = {"R. S, Kamath" and "R. K, Kamat"},
biburl = {https://www.bibsonomy.org/bibtex/2eab82ff3d300668a5e94e5c41d250568/ijitmc},
doi = {10.5121/ijitmc.2016.4102},
ee = {https://doi.org/10.1007/978-3-642-15231-3_32},
interhash = {b1a5e920300c8cc4c3c887c89c6ec50e},
intrahash = {eab82ff3d300668a5e94e5c41d250568},
journal = {International Journal of Information Technology, Modeling and Computing (IJITMC) },
keywords = {R classifiers crowd funding kickstarter learning machine prediction systems},
month = {February},
number = 1,
pages = 12,
timestamp = {2018-01-03T05:14:59.000+0100},
title = {SUPERVISED LEARNING MODEL FOR KICKSTARTER CAMPAIGNS WITH R MINING},
url = {http://aircconline.com/ijitmc/V4N1/4116ijitmc02.pdf},
volume = 4,
year = 2016
}