Why You Should Join Ontotext

Why You Should Join Ontotext

Telerik Academy Career Forum 2016 Marin Dimitrov (CTO)

Feb 2016

About Ontotext

2 Feb 2016 Ontotext @ Telerik Academy Career Forum 2016

About Ontotext

• We help companies find better answers in their own data − Founded in 2000, 70 employees

− HQ in Sofia, sales presence in NYC and London

• Major verticals

− Media & publishing

− Healthcare & life sciences

− Cultural heritage & digital libraries

− Government

− Financial information providers


Some of Our Customers


Smart Data Management

5

Semantic Graph Database

• Flexible graph data model

• Data integration

Enrichment, Search, Discovery

• Metadata driven content • Recommendations • Information discovery + exploration

Text Mining & Interlinking

• Organisations, people, locations, topics, relations

• Discover implicit relations • Reuse open knowledge graphs

Feb 2016 Ontotext @ Telerik Academy Career Forum 2016

Products & Solutions

#6 Feb 2016 Ontotext @ Telerik Academy Career Forum 2016









Technology

• Enterprise applications

• Databases

• Cloud Computing

• Natural Language Processing

• Machine Learning

• Knowledge Management / AI


Ontotext and AstraZeneca

12

Profile • Global, Bio-pharma company • $28 billion in sales in 2012 • $4 billion in R&D across three continents

Goals • Efficient design of new clinical studies • Quick access to all of the data • Improved evidence based decision-making • Strengthen the knowledge feedback loop • Enable predictive science

Challenges • Over 7,000 studies and 23,000 documents are difficult

to obtain • Searches returning 1,000 – 10,000 results • Document repositories not designed for reuse • Tedious process to arrive at evidence based decisions


Ontotext and EuroMoney

13

• Goals − Create a horizontal platform to

serve 100 different publications

− Platform which would include the latest authoring, storing, and display technologies including, semantic annotation, search and a triple store repository

• Challenges − Multiple domains covered

− Sophisticated content analytics including relation, template and scenario extraction


Ontotext and Financial Times

14

• Goals − Create a horizontal platform for

both data and content based on semantics and serve all functionality through it

• Challenges − Critical part of FT.COM

− GraphDB used not only for data, but for content storage as well

− Personalized recommendation based on user behavior and semantic context (Related Reads)


Ontotext and LMI

15

• Goals − Unlock large collections of complex

documents, e.g. regulations that come in 100s of pages in PDF

− Improve analyst productivity

• Challenges − Analysts taking hours to find,

download and search documents, using inaccurate keyword searches

− Needed a knowledge base to search quickly and guide the analysts


Research


The Team


The Team


The Team


The Team


Dec 2015 GraphDB Overview #21

Dec 2015 GraphDB Overview #22

The Team


Join Us

• Work with an innovative company

• Learn and work with leading edge technologies

• Work with top international companies and research organisations


Join Us


Join Us


Talk with Us

• [email protected]

• @ontotext

• https://www.facebook.com/Ontotext

• https://www.linkedin.com/company/ontotext-ad

• http://ontotext.com/company/#careers


mailto:[email protected]



https://www.facebook.com/Ontotext








https://www.linkedin.com/company/ontotext-ad










http://ontotext.com/company/#careers





Thank You! Why You Should Join Ontotext

Date post:	13-Apr-2017
Category:	Technology
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