Abstract
Distributional word similarity is most commonly perceived as a symmetric relation. Yet, one of its major applications is lexical expansion, which is generally asymmetric. This paper investigates the nature of directional (asymmetric) similarity measures, which aim to quantify distributional feature inclusion. We identify desired properties of such measures, specify a particular one based on averaged precision, and demonstrate the empirical benefit of directional measures for expansion. © 2009 ACL and AFNLP.
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CITATION STYLE
Kotlerman, L., Dagan, I., Szpektor, I., & Zhitomirsky-Geffet, M. (2009). Directional distributional similarity for lexical expansion. In ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf. (pp. 69–72). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1667583.1667606
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