ONTOLOGY BASED TECHNICAL SKILL SIMILARITY

Online job boards have become a major platform for technical talent procurement and job search. These job portals have given rise to challenging matching and search problems. The core matching or search happens between technical skills of the job requirements and the candidate\u27s profile or keywords. The extensive list of technical skills and its polyonymous nature makes it less effective to perform a direct keyword matching. This results in substandard job matching or search results which misses out a closely matching candidate on account of it not having the exact skills. It is important to use a semantic similarity measure between skills to improve the relevance of the results. This paper proposes a semantic similarity measure between technical skills using a knowledge based approach. The approach builds an ontology using DBpedia and uses it to derive a similarity score. Feature based ontology similarity measures are used to derive a similarity score between two skills. The ontology also helps in resolving a base skill from its multiple representations. The paper discusses implementation of custom ontology, similarity measuring system and performance of the system in comparing technical skills. The proposed approach performs better than the Resumatcher system in finding the similarity between skills. Keywords

Collaborative management of KYOTO Multilingual Knowledge Base: the Wikyoto Knowledge Editor

In this paper we introduce the Wikyoto Knowledge Editor, the wiki Web-based environment where the multilingual and multicultural community of KYOTO users interacts to maintain and extend, with respect to their particular domain of interest, the background knowledge resources of the KYOTO system, constituting the Multilingual Knowledge Base. KYOTO is a knowledge-driven system for fact mining from a multilingual collection of information sources concerning a specific domain of interest. Facts are mined from relevant documents that are linguistically and semantically annotated exploiting the Multilingual Knowledge Base, made of several languagespecific WordNets all referred to a common Central Ontology