26 Sep 2018
by Dr. Alessandro Negro, Dr. Vlasta Kůs
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.
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17 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
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.
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10 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
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 with external information (such as connecting people in a financial document with information from a business registry)
- relating causes (e.g weather conditions, accidents, regulatory changes) with effects (e.g. flight or tram delay, stock price changes)
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03 Sep 2018
by Dr. Vlasta Kůs, Dr. Alessandro Negro
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.
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02 Sep 2018
by Vince Bickers
Neo4j
State Machine
Optimisation Problems
Shortest Path
Introduction
In 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.
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26 Mar 2018
by Luke Housego
GraphAware
Nearly six years ago I started reading about this thing called Graph Data. Now unlike almost everyone in the modern world of Graph, I am not a coder. I was once upon a time but it has been many years since I typed a line of code. No I do not have a GitHub login. As an enterprise architect I often joke that I do powerpoint for a living. But I could see how this re-envisioning of data and how it could be used would transform enterprises. It is not just a technical change. It changes everything. People. Organisation. Knowledge. Processes. Products. Services. And yes, technology too.
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28 Feb 2018
by Eric Spiegelberg
Neo4j
The GraphAware Audit Module seamlessly and transparently captures the full audit history who, when, and how a graph was modified.
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03 Jan 2018
by Eric Spiegelberg
Neo4j
Causal Cluster
Docker
SDN
OGM
Enterprise IT requirements are demanding and solutions are expected to be reliable, scalable, and continuously available. Databases accomplish this through clustering, the ability of several instances to connect and conceptually appear and operate as a single unit.
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27 Dec 2017
by Luanne Misquitta
Neo4j
GraphAware
What a year it’s been for all of us at GraphAware!
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25 Nov 2017
by Eric Spiegelberg
Neo4j
Spring
Spring and Spring Boot have become the Swiss Army knife of Java software development, offering dozens of useful modules across a wide range of concerns.
One such module is Spring Boot Actuator, a sub-project of Spring Boot, that offers built-in, production-grade functionality to help monitor and interact with an application. Numerous endpoints are included that provide a wealth of information that, among others, include auditing, configuration, environment, and health details.
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