Social Interactome Recommender Project

Kinaman, Trevor; Baehre, Andrew; Gray, Colin

Social Interactome Recommender Project

dc.contributor.author	Kinaman, Trevor	en
dc.contributor.author	Baehre, Andrew	en
dc.contributor.author	Gray, Colin	en
dc.date.accessioned	2016-05-11T03:07:23Z	en
dc.date.available	2016-05-11T03:07:23Z	en
dc.date.issued	2016-05-05	en
dc.description	Contains a Word document and PDF of the final report, and the Powerpoint and PDF for our final presentation.	en
dc.description.abstract	Our team is working with the Social Interactome team to assist in coding the recommender functionality for the Social Interactome network. That is supported by a website and system (modified version of Friendica) designed by the Social Interactome team to help recovering addicts. The team used Python to parse participant’s answers to survey questions, and applied an algorithm to that data to show each participant's most favorable friend matches. The team is working in concert with Prashant Chandrasekar, a Graduate Research Assistant (GRA). He provided us access to the participant’s answers to survey questions. As more and more surveys are filled out by users the team will continue to refine their algorithm to accommodate that extra data. As a further step we will work towards a hybrid recommender which will incorporate not only content, but also collaborative-based recommending.	en
dc.description.sponsorship	NIH Grant 1R01DA039456-01	en
dc.description.sponsorship	Prashant Chandrasekar	en
dc.identifier.uri	http://hdl.handle.net/10919/70956	en
dc.language.iso	en_US	en
dc.rights	In Copyright	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject	Friendica	en
dc.subject	SIRecommender	en
dc.subject	Similarity Matrix	en
dc.subject	Homophily	en
dc.subject	Social Interactome	en
dc.subject	recommender	en
dc.subject	Addiction Recovery Research Center	en
dc.title	Social Interactome Recommender Project	en
dc.type	Presentation	en
dc.type	Software	en
dc.type	Report	en