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Automatically extracting actionable knowledge from on line social media has attracted a growing interest from both academia and the industry. However, little clarity exists in relation to what actionable knowledge is, whether it can be measured and where it is more likely to be found. This paper makes an attempt at answering the above questions by gaining a(More)
As short free text user-generated reviews become ubiquitous on the social web, opportunities emerge for new approaches to recommender systems that can harness users " reviews in open text form. In this paper we present a first experiment towards the development of a hybrid recommender system which calculates users " similarity based on the content of users(More)
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