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

Autoren Lorena Paoletti
Jorge Martinez Gil
Klaus-Dieter Schewe
Editoren
TitelTop-k matching queries for filter-based profile matching in knowledge bases
BuchtitelDatabase and Expert Systems Applications - Proc. DEXA 2016, Part II
Typin Konferenzband
VerlagSpringer
SerieLecture Notes in Computer Science
Band9828
ISBN978-3-319-44405-5
DOI10.1007/978-3-319-44406-2_23
MonatSeptember
Jahr2016
Seiten295-302
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.