Facebook, Inc.

Fang Xia

Bryan Kauder

Jonathan Michael Arfa

Nikhil Girish Nawathe

In one embodiment, a method includes receiving a request to identify a similarity in public sentiments for each pair from a plurality of entities from a second computing device, where the request includes names of the plurality of entities, accessing a table of word vector relationships, where the table of word vector relationships includes a plurality of unique n-grams and their corresponding word vectors, and where 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 word vectors corresponding to each of the names using the table, calculating, for each of the word vectors, a similarity metric to each of the word vectors, and sending a response message to the second computing device, where the response message includes calculated similarity metrics corresponding to all the pairs of the word vectors.

Consumer insights analysis by identifying a similarity in public sentiments for a pair of entities

In one embodiment, a method includes receiving a request to identify public sentiments for one or more entities from a second computing device, where each of the attribute n-grams represents an attribute among a plurality of pre-determined attributes, accessing a table of word vector relationships, looking up entity word vectors corresponding to each of the names for the one or more entities and attribute word vectors corresponding to each of the plurality of attribute n-grams using the table, calculating, for each of the entity word vectors, a similarity metric to each of the attribute word vectors, and sending a response message to the second computing device, where the response message includes calculated similarity metrics corresponding to all the pairs of an entity word vector and an attribute word vector.

Growing community of inventors

Redwood City, CA, United States of America

Fang Xia