Assume that EMB(w) is the word embedding for a word, w, computed by some common technique for computing word embeddings (e.g., word2vec). Consider the vector obtained by the following vector arithmetic: EMB("Japan") + EMB("Paris") - EMB("Tokyo"). Other than the words that already related to this equation, what word's embedding would likely be close to the result? Briefly explain (in one sentence) your answer.
Assume that EMB(w) is the word embedding for a word, w, computed by some common technique for computing word embeddings (e.g., word2vec). Consider the vector obtained by the following vector arithmetic: EMB("Japan") + EMB("Paris") - EMB("Tokyo"). Other than the words that already related to this equation, what word's embedding would likely be close to the result? Briefly explain (in one sentence) your answer.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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- Assume that EMB(w) is the word embedding for a word, w, computed by some common technique for computing word embeddings (e.g., word2vec). Consider the
vector obtained by the following vector arithmetic: EMB("Japan") + EMB("Paris") - EMB("Tokyo"). Other than the words that already related to this equation, what word's embedding would likely be close to the result? Briefly explain (in one sentence) your answer.
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