An integrated hybrid recommendation model using graph database
Angira Amit Patel, Jyotindra N. Dharwa · 2016
Graph database is revealed as alternative of traditional relation database for the reason that graph is flexible and self-explaining structure, which can cope with any kind of complex structure. Recently, graph database is extensively used to represent specially multi linked data of web, RDF data, social network, chemical structure, gene, network structure, publication links, and many more. This research illustrates potential use of graph database for recommendation system along with its convenience to develop hybrid recommendation system. Here, use of property graph model is demonstrated for solution of state-of-affairs hybrid recommendation system, complexity of beneath integrated data structure and required course of actions. This investigation anticipates an appropriate use of graph database to integrate various recommendation algorithms like content based recommendation; utility based recommendation as well as knowledge based recommendation. The main intention behind development of hybrid model is that helps in solving challenges of real world like cold start and many more. This research provides complete guidelines to anyone who wants to implement graph database for recommendation system along with various recommendation algorithms.