Ontotext: Integrated Text Mining and Triplestores, a form of graph database

Tags: Graph Databases, Ontotext, RDF, Text Mining, Triplestore

Learn about 2 hot trends: RDF triplestores, a form of graph database, and the use of text mining to extract meaning from Big Data, and how Ontotext enables both. Free eval, Feb 26 webinar, and more.

Free evals, a live webinar and an informative blog post

Ontotext - Making Sense of Text and Data

360 Degrees of Semantics:
Integrated Text Mining & Triplestores

RDF triplestores, a form of graph database, are getting hot. What’s driving adoption? Simply put, it is the need to analyze connections between entities. How are people connected? What servers are affected by suspicious cyber traffic? Which companies are subsidiaries? Depending on your data, the analysis you can do is endless.

There’s a second hot trend in big data - the use of text mining to extract meaning from monumental volumes of unstructured data.

A complete semantic solution combines the two in a unique way. Imagine if you could analyze text, extract and classify entities, identify relationships between entities and automatically store results in a graph database. imagine powering tour search and discovery applications with one integrated solution. True meaning is one query away.

Over 15 years ago, Ontotext started building this platform. Here’s where you can learn more:

Graph Databases are Hot! – Read about the top reasons why buyers use RDF triplestores
S4 – The Self Service Semantic Suite – A webinar by industry veteran Marin Dimitrov on how you can apply S4 in the cloud.
The Full Semantic Circle – A new blog post about the integration between text mining and triplestores.

Ontotext is powering the world’s enterprise semantic solutions. Learn more at www.ontotext.com