Semantic-Based Top-k Retrieval for Competence Management

Abstract

Abstract. We present a knowledge-based system, for skills and talent management, exploiting semantic technologies combined with top-k retrieval techniques. The system provides advanced distinguishing features, including the possibility to formulate queries by expressing both strict requirements and preferences in the requested profile and a semantic-based ranking of retrieved candidates. Based on the knowledge formalized within a domain ontology, the system implements an approach exploiting top-k based reasoning services to evaluate semantic similarity between the requested profile and retrieved ones. System performance is discussed through the presentation of experimental results.

Careprofsys – An Ontology for Career Development in Engineering Designed for the Romanian Job Market

“…The Skill ontology was introduced to match the job requirements with applicants' profiles and obtain a ranked list of the most suitable applicants. Similar systems were introduced by [17,18]. [19] created an ontology for identifying employees to be assigned to specific company positions.…”

Fudge: Fuzzy ontology building with consensuated fuzzy datatypes

“…Fuzzy ontologies have already proved to be useful in several applications, such as information retrieval [8,44,50], Semantic Web and the Internet [42], ambient intelligence [15], ontology merging [46], matchmaking [37], decision making [33], summarization [25], construction [19], robotics [17], diabetes diagnosis [18], design [35], human resources [43], decision making [41], gait recognition [22], and many others [28,38]. For a more detailed overview, we refer the reader to [11].…”

From Fuzzy to Annotated Semantic Web Languages

“…Fuzzy set theory and fuzzy logic [318] have proved to be suitable formalisms to handle fuzzy knowledge. Not surprisingly, fuzzy ontologies already emerge as useful in several applications, such as information retrieval [3,67,175,298,299,311,319], recommendation systems [71,164,224,314], image interpretation [95,96,97,215,254,258,259], the Semantic Web and the Internet [80,226,241], ambient intelligence [103,104,174,235], ontology merging [75,301], matchmaking [2,79,227,228,229,230,231,296,297], decision making [281], summarization [163], robotics [111,112], machine learning [166,167,168,169,170,…”