What to be? - Electronic Career Guidance Based on Semantic Relatedness (2007)
| Venue: | In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL’2007 |
| Citations: | 15 - 8 self |
BibTeX
@INPROCEEDINGS{Gurevych07whatto,
author = {Iryna Gurevych and Christof Müller and Torsten Zesch},
title = {What to be? - Electronic Career Guidance Based on Semantic Relatedness},
booktitle = {In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL’2007},
year = {2007},
pages = {1032--1039}
}
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Abstract
We present a study aimed at investigating the use of semantic information in a novel NLP application, Electronic Career Guidance (ECG), in German. ECG is formulated as an information retrieval (IR) task, whereby textual descriptions of professions (documents) are ranked for their relevance to natural language descriptions of a person’s professional interests (the topic). We compare the performance of two semantic IR models: (IR-1) utilizing semantic relatedness (SR) measures based on either wordnet or Wikipedia and a set of heuristics, and (IR-2) measuring the similarity between
