@conference {1975726,
	title = {BEHAVIOR THEORY ENABLED GENDER CLASSIFICATION METHOD},
	booktitle = {the Fifteeth workshop on e-Business (WeB 2016) in Dublin},
	year = {2017},
	month = {2017},
	keywords = {BIS, Business Analytics},
	author = {Wang,Jing and Yan,Xiangbin and Zhu,Bin}
}
@booklet {1985036,
	title = {Gender Classification for Product Reviewers in China: A Data-Driven Approach},
	year = {2013},
	month = {2013},
	abstract = {While it is crucial for organizations to automatically identify the gender of participants in product discussion forums, they may have difficulties adopting existing gender classification methods because the associations between the linguistic features used in those studies and gender type usually varies with context. The prototype system we propose to demo validates a framework for the development of gender classification that uses a more {\textquotedblleft}data-driven{\textquotedblright} approach. It constantly extracts content-specific features from the discussion content. And the system could automatically adjust itself to accommodate the contextual changes in order to achieve better classification accuracy.},
	keywords = {BIS, Business Analytics},
	url = {http://www.som.buffalo.edu/isinterface/wits2013/},
	author = {Zhu,Bin and Yan,Xiangbin and Wang,Jing}
}
