Abstract

As the increase of users in social networking sites gives rise to complex relation between the users, which often leads to understand the group of users with similar taste. Now days, this is a one of the growing research area to find the similar users in the relational graph database. Many systems are been introduced to identify the matching sub graphs using similarity between the users. This often yields not much appropriate results due to strict similarity measures. So proposed system uses a technique of identifying correlation between the users for the fired query using pattern identification by incorporating frequent pattern analysis and Pearson correlation which is catalyzed by strong pruning techniques.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.