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Title: Tweetalyser : a Twitter based data mining system with recommendation capabilities
Authors: Montebello, Matthew
Camilleri, Vanessa
Refalo, Maria
Keywords: Recommender systems (Information filtering)
Web 2.0
Social networks
Text processing (Computer science)
Data mining
Issue Date: 2011
Publisher: IAmLearn
Citation: Montebello, M., Camilleri, V., & Refalo, M., (2011). Tweetalyser : a Twitter based data mining system with recommendation capabilities. 10th International Conference on Contextual and Mobile Learning, mLearn2011, Beijing. 349-356.
Abstract: Tweetalyser scientifically processes and stires the free information available in user tweets and extracts facts which are then used for item recommendation. The system proves that it is easy to tap into this data mine using low footprint social network APIs and third party technologies, in conjunction with the appropriate scientific algorithms. When at its full potential, Tweetalyser is able to provide useful information about a user which, when put in the right context can uncover true knowledge. From a social networking point of view, Tweetalyser has the potential of recommending and thus increasing attendance to various events. It also attracts newcomers who in turn crowdsource useful data elements to construct a truly formidable knowledge system.
Appears in Collections:Scholarly Works - FacICTAI

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