Human Resources Management

A Smart Approach for Matching, Learning and Querying Information from the Human Resources Domain

In this paper, we face the complex problem of timely, accurate and mutually satisfactory mediation between job offers and suitable applicant profiles by means of different semantic processing techniques.

 

For more information, please refer to:

Reference: Jorge Martinez-Gil, Alejandra Paoletti, Klaus-Dieter Schewe. A Smart Approach for Matching, Learning and Querying Information from the Human Resources Domain. Communications in Computer and Information Science, Springer Verlag (Germany), pp.157-167, 2016

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

We propose 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.

 

For more information, please refer to:

Reference:

Alejandra Lorena Paoletti, Jorge Martinez-Gil, Klaus-Dieter Schewe: Top-k Matching Queries for Filter-Based Profile Matching in Knowledge Bases. DEXA (2) 2016: 295-30

Human Resources Management

By Jorge Martinez-Gil

Human Resources Management

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