Meta Platforms, Inc.
Determining related query terms through query-post associations on online social networks

Abstract:

In one embodiment, a method includes receiving an text query, identifying and ranking multiple content objects corresponding to character strings from the text query. A computing system determines the ranking based on an analysis of the association between the terms in the content objects and the n-grams in the query using term frequency-inverse document frequency (TF-IDF) scores of the terms. The computing system accesses a query-term index to determine the TF-IDF scores for the terms, wherein the query-term index includes multiple entries corresponding to multiple terms extracted from multiple prior queries. Each entry in the query-term index includes a query term, one or more related terms extracted from content objects of the online social network matching the prior query term, and a term frequency-inverse document frequency (TF-IDF) score for the respective related terms.