Meta Platforms, Inc.
Consumer insights analysis using word embeddings
Last updated:
Abstract:
In one embodiment, a method includes receiving a request to generate k keywords each of which is semantically related to a particular subject, where the request includes an input n-gram representing the particular subject, accessing a table of word vector relationships, where the table includes a plurality of unique n-grams and their corresponding word vectors, and wherein each of the word vectors represents a semantic context of a corresponding n-gram as a point in a d-dimensional embedding space, looking up, using the table, a first word vector corresponding to the input n-gram, selecting k word vectors closest to the first word vector in the embedding space using the table and based on a similarity metric, identifying, for each of the selected word vectors, a corresponding n-gram by looking up the selected word vector in the table, and sending a response message including the identified n-grams.
Utility
4 Jan 2018
13 Oct 2020