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Classifying search queries on online social networks

  • US 10,726,022 B2
  • Filed: 08/26/2016
  • Issued: 07/28/2020
  • Est. Priority Date: 08/26/2016
  • Status: Expired due to Fees
First Claim
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1. A method comprising:

  • receiving, from a client system of a first user of an online social network, a search query inputted by the first user, wherein the search query comprises one or more n-grams;

    calculating a needle-confidence score for the search query, wherein the needle-confidence score is calculated by a needle-intent classifier based on at least the n-grams of the search query and a language model analysis of the n-grams, and wherein the needle-confidence score represents a probability that the search query was intended as a needle search for specific content objects associated with the first user'"'"'s social network connections and previously viewed by the first user;

    classifying the search query as a needle search if the calculated needle-confidence score is above a threshold confidence score;

    identifying, responsive to the classification of the search query as a needle search, one or more content objects matching the search query, each identified content object being associated with the first user'"'"'s social network connections and previously viewed by the first user; and

    generating a plurality of search-result modules, each search-result module comprising one or more search results referencing one or more content objects matching the search query, respectively, wherein one of the search-result modules is a social module, wherein a number of search results in the social module is based on the classification of the search query as a needle search, and wherein one or more of the search results in the social module reference one or more of the identified content objects associated with the first user'"'"'s social network connections and previously viewed by the first user.

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