GraphAware Blog

Find out what's new in the world of mission-critical graph analytics.

Using NLP + Neo4j for a Social Media Recommendation Engine

04 Oct 2016 by Alessandro Negro · 5 min read Neo4j NLP

In recent years, the rapid growth of social media communities has created a vast amount of digital documents on the web. Recommending relevant documents to users is a strategic goal for the effectiveness of customer engagement but at the same time is not a trivial problem.

Internationalization with CypherMessageSource, Spring and Neo4j

29 Sep 2016 by Eric Spiegelberg, Guest Author · 6 min read Neo4j SDN Internationalization Localization

Whether you realize it or not, the software you create has a global market. Perhaps more so than any other product in any other industry,code that may start as a small, individual effort has the potential to rapidly blossom into a product used around the world.While it is not always obvious that your application can or will have such wide usage, it is in your best interest to maximizethe number of organizations and people you can reach. This means it is important to ensure your software is internationalized and localized.

Neo4j as a Key Player in Human Capital Management

19 Jul 2016 by Luanne Misquitta · 7 min read Neo4j HCM PeopleAnalytics HR HRTech

In the Bersin Predictions for 2016 report, Josh Bersin states that “it feels as though everything in the world of talent is changing – from the way we recruit and attract people, as well as how we reward them, to the way we learn, and how we curate and manage our entire work-life experience”[1].

Graph-Aided Search - The Rise of Personalised Content

20 Apr 2016 by Alessandro Negro, Christophe Willemsen · 26 min read Neo4j Cypher Recommendations Elasticsearch

In our previous blog postwe introduced the concept of Graph Aided Search. It refers to a personalised user experience during search where theresults are customised for each user based on information gathered about them (likes, friends, clicks, buying history, etc.).This information is stored in a graph database and processed using machine learning and/or graph analysis algorithms.

(Un)common Use Cases for Graph Databases

18 Apr 2016 by Michal Bachman · 3 min read Neo4j Beginner Modelling

At GraphAware, we live and breathe Neo4j. For three years, we have been helping customers around the world embrace thisamazing technology as a solution to many interesting problems. Mainstream applications of graphs, such as real-timerecommendations, fraud detection, impact analysis, and graph-aided search, have been getting a lot of media attention.