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Virtual-Citation-Proximity

VCP Virtual Citation Proximity (VCP) which uses Siamese Neural Network along with the notion of citation proximity analysis and content-based filtering. To train this model, actual distance between the two citations in a document is used as a ground truth, this distance is basically the word count between the two citations. VCP is trained on a Wikipedia articles for which the actual word count is available which is used to calculate the similarity between the documents. This can be used to calculate relatedness between two documents in a way they would have been cited in the proximity even if the documents are uncited. This is a very simple Siamese neural network, yet it gave better result then the previous implementation of VCP by Paul Molloy.

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  • Python 100.0%