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Deep Dive into Neo4j 3.5 Full Text Search

Deep Dive into Neo4j 3.5 Full Text Search

11 Jan 2019 by Christophe Willemsen · 15 min read Neo4j Cypher Search

In this blog we will go over the Full Text Search capabilities available in the latest major release of Neo4j.Contrary to our usual blogs, the content will rather focus on the underlying search engine used by Neo4j, that is Apache Lucene in version 5.5.5 .What exactly is Search ?Search is an interaction between a user and a search engine. The user has an information need at hand and attempts to satisfy it by providing a search with adequate constraints.The search engine uses those constraints to collect matching results and return them to the user.What is a Search Engine ?A search...

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.Over in Australia, various government entities have showed keen interest in auto-classification, simplifying organisational movement, enriching original documents, and security and...

Integration testing with Docker Neo4j image and Testcontainers

16 Dec 2018 by František Hartman · 8 min read Testing Docker Neo4j

Automated testing is the cornerstone of any successful software project.Applications using the Neo4j database are no exception. This blog postshows how to use the Neo4j Dockerimage and the Testcontainerslibrary for integration testing inJava using JUnit.This blog post shows examples in Java. Testcontainers library has beenported to many other languages so the same approach and principles canbe applied. Check out theTestcontainersgithub page.MotivationNeo4j already provides a testing harness to start a temporary databasewithin tests, either manually or through a JUnit rule. To use thisharness one must include theneo4j-harnessmaven artifact, together with whole Neo4j database as a testdependencyto the project. This inevitably pollutes...

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.The close alignment between GraphAware and Neo4j is strengthened by this move, and bolstered by GraphAware’s substantial investment in Neo4j graph database deployment best practices over the last half-decade. This includes Neo4j-specific consulting, products and training- helping to accelerate Neo4j use and adoption all over the globe.Neo4j’s President and COO Lars Nordwall said of GraphAware:“GraphAware is one of our earliest and most...

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.Without knowing your core business, I...

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.The data, in its native form, is completely useless because it doesn’t provide any value. It is sparse, distributed and unstructured – it is chaotic.To make sense of the data, we have to transform and organize it – a process that produces information. However, for the information to...

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.What’s out there?Extracting sentiments from texts is a difficult task. Many models predict...

Deep text understanding combining Graph Models, Named Entity Recognition and Word2Vec

10 Sep 2018 by Dr. Vlasta Kůs, Dr. Alessandro Negro · 15 min read word2vec NLP NER Knowledge Graph

One of the key components of Information Extraction (IE) and Knowledge Discovery (KD) is Named Entity Recognition, which is a machine learning technique that provides us with generalization capabilities based on lexical and contextual information. Named Entities are specific language elements that belong to certain predefined categories, such as persons names, locations, organizations, chemical elements or names of space missions. They are not easy to find and subsequently classify (for example, organizations and space missions share similar formatting and sometimes even context), but having them is of significant help for various tasks: improving search capabilities relating documents among themselves or...

Advanced Document Representation

03 Sep 2018 by Dr. Vlasta Kůs, Dr. Alessandro Negro · 15 min read doc2vec NLP Knowledge Graph

Representation is one of the most complex and compelling tasks in machine learning. The way in which we represent facts, events, objects, labels, etc. affects how an autonomous learning agent can analyze them and extract insights, make predictions and deliver knowledge.In this blog post, we focus on natural language processing and how to represent textual entities such as words, sentences, paragraphs or whole documents. Dealing with text is hard because, from the “algorithm” perspective, it is just a list of strings or characters. If we want to efficiently grab text and use it in various analytics tasks, we need to...

Solving the bucket-filling problem with Neo4j

02 Sep 2018 by Vince Bickers · 7 min read Neo4j State Machine Optimisation Problems Shortest Path

IntroductionIn the bucket filling problem you are given two empty buckets, each of a certain capacity, and a large supply of water. By filling, emptying and transferring water between the two buckets, you must try to end up with a situation where one of the buckets contains a required volume of water, or where both buckets together contain the required volume.One popular instance of the problem has two buckets with a capacity of 5 and 3 litres respectively, with the goal being to find a solution where one bucket contains exactly 4 litres. One solution is shown below: Step Action...