• Anuja Krishna Gaikwad

As the adoption of social media has been exponentially increasing, there has been an increase in the amount and frequency of data being shared between the users. Due to the increase in the user base of the websites, it is highly beneficial for the organizations to retrieve users with similar interests into the relational graph database. There has been substantial research in this area for the extraction of the similarity in the users with the help of identifying the matching sub-graphs. But this process is cumbersome and usually leads to a lot of false positives. Therefore, the proposed system solves this problem by utilizing pattern identification for determining the similarity between users by introducing pattern matching and hyper graph analysis accompanied by strong pruning techniques.

Hyper graph, Neo4j, Pattern matching, preprocessing

"AN ADAPTIVE GRAPH DATA EXTRACTION USING PATTERN MATCHING AND HYPER GRAPH FORMATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.183-190, April-2019, Available :http://www.jetir.org/papers/JETIR1904M29.pdf

"AN ADAPTIVE GRAPH DATA EXTRACTION USING PATTERN MATCHING AND HYPER GRAPH FORMATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp183-190, April-2019, Available at : http://www.jetir.org/papers/JETIR1904M29.pdf