| Popis: |
Recommender systems are envisioned and design to serve automatic recommendations for various services and products to active consumer. Such systems can find similar items and sort to generate top N suggestions as per users past transaction, location, knowledge, profiles, preferences or choices of otherpeople. This research illustrates potential use of graph-based model intended for recommendation system and designed for various domains. The ultramodern graph technology and state-of-the-art graph query tool is prime motivation behind this research work. The implementation has been carried out with profound online graph management tool known as ‘neo4j’ and recommendation algorithm has been executed with graph query language called ‘Cypher’. The experiment and evaluation shows success of proposed model for increasing efficiency of the system which is emerging need of the present. The outcome of this research has great potential which can be put into practice and it can offer course of action for advance technical revolution in forthcoming era of Big data. This research also encourages anyone who wants to implement graph-based model for recommendation system. |
