GraphAware Blog

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

Lean Dependencies- Reduce Project Delivery Chaos with Graphs

Lean Dependencies- Reduce Project Delivery Chaos with Graphs

20 Feb 2019 by Luanne Misquitta · 6 min read Neo4j Beginner

Dependencies, like graphs, are everywhere. Achieving a goal is rarely possible in a vacuum and requires collaboration between individuals and/or processes.Eliminating dependencies completely is unrealistic- they are a part of life- but they can be streamlined to improve efficiency and reduce friction.

Graph Technology Landscape 2019

Graph Technology Landscape 2019

01 Feb 2019 by Janos Szendi-Varga · 8 min read Neo4j GraphAware

Few years ago I decided that one day I would create a Graph Technology Landscape map, which would be useful for everyone who wants to discover the players around graph technologies. I started to collect the companies and products, but my research has never manifested into a proper blog post. Till now. I am happy to announce, that the first version of my landscape is published, I hope we can consider this as a start of a long journey.

Speaker identification meets graphs

Speaker identification meets graphs

28 Jan 2019 by Jan Zak · 7 min read Analytics Connected Data Community Detection Voice

In social network analysis, a conventional approach relies heavily on available metadata, allowing to match a virtual entity (social network account) to a real-world entity (person, company) in the network. However, a single person using multiple accounts for any reason obviously breaks the connection, forming multiple virtual entities in the network. Or multiple people can share their account, forming a single virtual entity in the network. If these cases are not taken into account, they can affect reliability of social network analysis significantly without any warning, possibly leading to misinformed decisions and further bad consequences.

This year at GraphAware

This year at GraphAware

27 Dec 2018 by Luanne Misquitta · 4 min read Neo4j GraphAware

2018- it’s been such a whirlwind of activity at GraphAware, and we’re so proud of everything we’ve accomplished this year.In fact, we grew and grew, announcing ourselves in Australia and then, later in the year, expanding into the Americas.“Neo4j is one of the most disruptive and transformative technologies I have seen in my career,” said Kyle McNamara, CEO, Americas. His team are well on their way to increasing GraphAware’s presence and strengthening the already close bond we have with Neo4j.

GraphAware Announces Expansion into Americas

28 Nov 2018 by Kyle McNamara · 1 min read GraphAware

BOSTON, MA, Nov. 28th, 2018 – GraphAware, a leading Neo4j consulting practice, today announced the official launch of its US entity GraphAware, Inc., headquartered in Boston, MA. This strategic investment by GraphAware aligns with Neo4j’s own rapid market expansion.

Why You Should Start Thinking About Your Organization as a Graph

22 Oct 2018 by Janos Szendi-Varga · 6 min read Knowledge Graph NLP Neo4j Connected Data Knowledge Platform

Do you think there is no space for a graph database in your company? Or it would be a huge effort to integrate a graph database into your product? I have to tell you: You can use a graph database like Neo4j without touching your product, and you can use it for managing your company’s knowledge as well as to improve your software development process. So, even if your business problem is not inherently graphy (hard to believe in 2018), there are a few reasons why you should think about your environment as a graph.

Bring Order to Chaos: A Graph-Based Journey from Textual Data to Wisdom

26 Sep 2018 by Dr. Alessandro Negro, Dr. Vlasta Kůs · 12 min read NLP Knowledge Graph Sentiment Analysis word2vec NER

Data is everywhere. News, blog posts, emails, videos and chats are just a few examples of the multiple streams of data we encounter on a daily basis. The majority of these streams contain textual data – written language – containing countless facts, observations, perspectives and insights that could make or break your business.

Caring about sentiment: how to get the most from people feelings

17 Sep 2018 by Dr. Vlasta Kůs, Dr. Alessandro Negro · 9 min read Sentiment Analysis doc2vec NLP Knowledge Graph

It is often useful to relate a piece of text with the sentiment expressed in it. Extracting and processing sentiments from text provides not only a new emotional access pattern to your corpus but also new knowledge which can reveal new insights. Suppose you want to build a recommendation engine which leverages reviews to spot detailed strengths and weaknesses of different hotels, such as good location but bad staff. Or, it certainly makes a difference whether an article talks about your organization in a positive or negative manner.