Profile-based recommendation: A case study in a parliamentary context
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Recommender systemInformation FilteringInformation retrievalParliamentary DocumentsUser profiles
Journal of Information Science 2017, Vol. 43(5) 665–682
SponsorshipThis research has been supported by the Spanish ‘Ministerio de Economı́a y Competitividad’ under project TIN2013-42741-P and the European Regional Development Fund.
In the context of e-government and more specifically that of parliament, this paper tackles the problem of finding Members of Parliament (MPs) according to their profiles which have been built from their speeches in plenary or committee sessions. The paper presents a common solution for two problems: firstly, a member of the public who is concerned about a certain issue might want to know who the best MP is for dealing with their problem (recommending task); and secondly, each new piece of textual information that reaches the house must be correctly allocated to the appropriate MP according to its content (filtering task). This paper explores both these ways of searching for relevant people conceptually by encapsulating them into a single problem: that of searching for the relevant MP’s profile given an information need. Our research work proposes various profile construction methods (by selecting and weighting appropriate terms) and compares these using different retrieval models to evaluate their quality and suitability for different types of information needs in order to simulate real and common situations.