Cross-domain citation recommendation based on hybrid topic model and co-citation selection citation selection

Tantanasiriwong, Supaporn and Guha, Sumanta and Janecek, Paul and Haruechaiyasak, Choochart and Azzopardi, Leif (2017) Cross-domain citation recommendation based on hybrid topic model and co-citation selection citation selection. International Journal of Data Mining, Modelling and Management, 9 (3). pp. 220-236. ISSN 1759-1163 (https://doi.org/10.1504/IJDMMM.2017.086566)

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Abstract

Cross-domain recommendations are of growing importance in the research community. An application of particular interest is to recommend a set of relevant research papers as citations for a given patent. This paper proposes an approach for cross-domain citation recommendation based on the hybrid topic model and co-citation selection. Using the topic model, relevant terms from documents could be clustered into the same topics. In addition, the co-citation selection technique will help select citations based on a set of highly similar patents. To evaluate the performance, we compared our proposed approach with the traditional baseline approaches using a corpus of patents collected for different technological fields of biotechnology, environmental technology, medical technology and nanotechnology. Experimental results show our cross domain citation recommendation yields a higher performance in predicting relevant publication citations than all baseline approaches.

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