Alejandra Lorena Paoletti, Jorge Martinez-Gil, Klaus-Dieter Schewe,
"Top-k Matching Queries for Filter-Based Profile Matching in Knowledge Bases"
, in Hartmann, Svenand Ma, Hui: Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II, Vol. 9828, Springer International Publishing, Cham, Seite(n) 295--302, 2016, ISBN: 978-3-319-44406-2
Original Titel:
Top-k Matching Queries for Filter-Based Profile Matching in Knowledge Bases
Sprache des Titels:
Englisch
Original Buchtitel:
Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II
Original Kurzfassung:
Finding the best matching job offers for a candidate profile or, the best candidates profiles for a particular job offer, respectively constitutes the most common and most relevant type of queries in the Human Resources (HR) sector. This technically requires to investigate top-k queries on top of knowledge bases and relational databases. We propose in this paper a top-k query algorithm on relational databases able to produce effective and efficient results. The approach is to consider the partial order of matching relations between jobs and candidates profiles together with an efficient design of the data involved. In particular, the focus on a single relation, the matching relation, is crucial to achieve the expectations.
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