document: Context-aware citation recommendation When you write papers , how many times do you want to make some citations at a place but you are not sure which papers to cite ? Do you wish to have a recommendation system which can recommend a small number of good candidates for every place that you want to make some citations ? In this paper , we present our initiative of building a context-aware citation recommendation system . High quality citation recommendation is challenging : not only should the citations recommended be relevant to the paper under composition , but also should match the local contexts of the places citations are made . Moreover , it is far from trivial to model how the topic of the whole paper and the contexts of the citation places should affect the selection and ranking of citations . To tackle the problem , we develop a context-aware approach . The core idea is to design a novel non-parametric probabilistic model which can measure the context-based relevance between a citation context and a document . Our approach can recommend citations for a context effectively . Moreover , it can recommend a set of citations for a paper with high quality . We implement a prototype system in CiteSeerX . An extensive empirical evaluation in the CiteSeerX digital library against many baselines demonstrates the effectiveness and the scalability of our approach .
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