Top-k matching queries for filter-based profile matching in knowledge bases

Authors Lorena Paoletti
Jorge Martinez Gil
Klaus-Dieter Schewe
Editors
Title Top-k matching queries for filter-based profile matching in knowledge bases
Booktitle Database and Expert Systems Applications - Proc. DEXA 2016, Part II
Type in proceedings
Publisher Springer
Series Lecture Notes in Computer Science
Volume 9828
ISBN 978-3-319-44405-5
DOI 10.1007/978-3-319-44406-2_23
Month September
Year 2016
Pages 295-302
SCCH ID# 1647
Abstract

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 investigating 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.