Implementing Semantics Based Cross domain Collaboration Recommendation in Biomedicine with a Graph Database
We describe a novel approach for cross domain recommendation for research collaboration. We first constructed a large Neo4j graph database representing authors, their expertise, current collaborations, and general biomedical knowledge. This information comes from MEDLINE and from semantic relations extracted with SemRep. Then, by using an extended literature based discovery paradigm, implemented with the Cypher graph query language, we recommend novel collaborations, which include author pairs, along with novel topics for collaboration and motivation for that collaboration. KeywordsResearch collaboration; Recommendation system; Literature based discovery; Semantic MEDLINE; Graph
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