Directional distributional similarity for lexical expansion

L Kotlerman; I. Dagan; I Szpektor; M. Zhitomirsky Geffet

Directional distributional similarity for lexical expansion

L Kotlerman, I. Dagan, I Szpektor, M. Zhitomirsky Geffet

Department of Information Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	American English
Title of host publication	The ACL-IJCNLP 2009 Conference
State	Published - 2009

Bibliographical note

Place of conference:Singapore

Cite this

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title = "Directional distributional similarity for lexical expansion",

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.",

author = "L Kotlerman and I. Dagan and I Szpektor and {Zhitomirsky Geffet}, M.",

note = "Place of conference:Singapore",

year = "2009",

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AU - Kotlerman, L

AU - Dagan, I.

AU - Szpektor, I

AU - Zhitomirsky Geffet, M.

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PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

M3 - Conference contribution

BT - The ACL-IJCNLP 2009 Conference

ER -

Directional distributional similarity for lexical expansion

Abstract

Bibliographical note

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Cite this