Paper: Calculating Semantic Distance Between Word Sense Probability Distributions

ACL ID W04-2411
Title Calculating Semantic Distance Between Word Sense Probability Distributions
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2004
Authors

Semantic similarity measures have focused on individual word senses. However, in many ap- plications, it may be informative to compare the overall sense distributions for two differ- ent contexts. We propose a new method for comparing two probability distributions over WordNet, which captures in a single measure the aggregate semantic distance of the com- ponent nodes, weighted by their probability. Previous such measures compute only the dis- tributional distance, and do not take into ac- count the semantic similarity between Word- Net senses across the distributions. To in- corporate semantic similarity, we calculate the (dis)similarity between two probability distri- butions as a weighted distance “travelled” from one to the other through the WordNet hierar- chy. We evaluate the mea...