Resources - videos - page 6

Videos, Slides, Case Studies and other GraphAware related resources

Neo4j Online Meetup #30: Spring Data Neo4j 5 and OGM3

19 Nov 2017 videos

SDN is a Spring Data project for Neo4j. It uses Neo4j-OGM under the hood (very much like Spring Data JPA uses JPA) and provides functionality known from the Spring Data world like repositories, derived finders or auditing. Neo4j recently released Spring Data 2.0 (Kay) / Spring Data Neo4j 5.0 and in this session we’ll show some of the new cool features. This release contains support for dynamic properties, schema based loading, field access only, and more.

Knowledge Graph Search with Elasticsearch — Luanne Misquitta and Alessandro Negro, GraphAware

16 Nov 2017 videos

In this talk, Luanne will share insights about the business value of knowledge graphs and their contribution to relevant search in an e-commerce domain for a Neo4j customer. With text search and catalog navigation being the entry point of users to the system and in fact, driving revenue, the talk will explain the challenges of relevant search and how graph models address them. Dr. Alessandro will then talk about various techniques used for information extraction and graph modelling. He will also demonstrate how to seamlessly introduce knowledge graphs into an existing infrastructure and integrate with other tools such as ElasticSearch, Kafka, Apache Spark, OpenNLP and Stanford NLP.

Cypher: Write Fast and Furious

08 Jun 2017 videos

Ever struggle with writes performance in Cypher? This Lightning talk is for you! In only 15 minutes, Christophe will show you some tips and tricks for making your Cypher write transactions as fast as possible.

The power of polyglot searching

02 Jun 2017 videos

In the previous years we have got the Polyglot Persistence. This is a fancy term which means that when storing data, it is best to use multiple data storage technologies, chosen based upon the way data is being used by. If we have multiple persistence, then sometimes we need polyglot operations. One of the most popular use case in Big Data is searching. Almost all websites provide a search function to their users, to be able to find what they are looking for. Usually it is an Apache Lucene based solution, like Elasticsearch or Solr. I will show you how to enrich this kind of searching with the power of graph based searches, and implement a polyglot search functionality, where the results are based on the cooperation of a search engine and a graph based real time recommendation.

Mining and Searching text with Graph Databases

02 Jun 2017 videos

A great part of the world’s knowledge is stored using text in natural language, but using it in an effective way is still a major challenge. Natural Language Processing (NLP) techniques provide the basis for harnessing this huge amount of data and converting it into a useful source of knowledge for further processing. It uses computer science, artificial intelligence and formal linguistics concepts to analyze natural language, aiming at deriving meaningful and useful information from text.