11.30 – 12.00 Semantic job search- showcase Jakub Zavrel, CEO Textkernel

ESCO and Semantic Search & Match for Jobs and People Brussels, 9/10 October 2017

What is Semantic Search? Find what you mean, not what you type Search for things, not for strings

Semantic Search & Match. Why? More relevant candidates, faster! 1. More candidates: Expanding words to concepts No guessing what candidate wrote in the resume 2. Relevant candidates: Better filtering and ranking Avoid wrong matches by understanding context 3. Work faster - Start working on the most promising candidates first - Be a great searcher without advanced Boolean search - Use documents (jobs, resumes) to start automated searches 2 word user query = 35+ system query

Three Elements of Semantic Search Document understanding Domain knowledge Machine Learning CV & job parsing Information extraction Taxonomies Ontologies Skills Keywords Algorithms learn from a large set of data Learning to Rank Deep Learning

job branch langskill location Match! Match! models construct the Search! Data Model out of extracted information. Vacancy Extraction job=Java Ontwikkelar city=Amsterdam langskill=Duits experience=7 CV Extraction job=Java Developer city=Amsterdam langskill=German experience=7 Match! Vacancy Match Normalizer job=23 branch=IT langskill=DE experience=5..10 loc=Amsterdam+10 CV Match Normalizer job=23 branch=IT langskill=DE experience=7 loc=Amsterdam Search! Data Model job branch langskill location experience The XML fits the Search! Data Model and is semantically enriched when INDEXING. The result is a QUERY that fits the Search! Data Model. It is semantically enriched when executed

ESCO – What it means for us Direct availability of semantic query enrichments in 26 EU languages (on top of 6 that we developed internally) Cross lingual search because of aligned taxonomies. Occupation to skills expansion for better search

Demo

Some numbers on coverage Numbers of results? Occupation ESCO Essential ESCO Optional TK Skills ICT Security Technician 2230 2255 ICT Network Technician 128 454 Data Scientist 21 92 200 Office Manager 23 187 9514 Sales Manager 17 47 164 Sales Assistant 1 543 Waiter/waitress 207 Receptionist 190 193 197

Some numbers on coverage How is the general coverage of the data by ESCO?

Some numbers on coverage How is the general coverage of the data by ESCO?

Summary Textkernel will support ESCO v1 in its Search & Match products. Direct availability of semantic enrichments in 26 EU languages. A standard to evolve. Further steps needed to address: Gap between ESCO terms and actual language use Maintenance process