Characterizing data using descriptive tokens

US2017193073A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2017193073-A1
Application numberUS-201514985230-A
CountryUS
Kind codeA1
Filing dateDec 30, 2015
Priority dateDec 30, 2015
Publication dateJul 6, 2017
Grant date

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Abstract

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In one embodiment, a method includes a computing device receiving postings from users of an online social networking system. A postings may include location data along with one or more tags that may describe the content of the posting. The computing device may identify regions and subregions from which the postings originated, and may determine a distribution of the tags according to two data dimensions: the ubiquity of the tags across the regions, and the ubiquity of the tags across the subregions. Based on the distribution, the computing device may create a neighborhood characterization to accurately describe one or more subregions. The computing device may also determine applications for the neighborhood characterization.

First claim

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What is claimed is: 1 . A method comprising: by a computing device, receiving postings submitted by one or more users of a social-networking system, wherein a posting comprises location data and one or more tags; by the computing device, for each of the postings, based on the location data, identifying one of a plurality of regions and one of a plurality of subregions of the regions; by the computing device, determining a distribution of the tags according to two data dimensions, a first one of the data dimensions comprising a degree of ubiquity of the tags across the regions, a second one of the data dimensions comprising a degree of ubiquity of the tags across the subregions in the regions; by the computing device, based on the distribution, identifying one or more of the tags that are common to multiple ones of the subregions across the different regions; by the computing device, generating a neighborhood characterization based on the identified tags; and by the computing device, applying the neighborhood characterization. 2 . The method of claim 1 , wherein a region comprises a state, province, county, or a city, and wherein a subregion comprises a neighborhood. 3 . The method of claim 1 , further comprising: generating a visual representation of the distribution of the tags. 4 . The method of claim 1 , wherein generating a neighborhood characterization based on the identified tags comprises applying natural language processing to content associated with the postings to generate the neighborhood characterization. 5 . The method of claim 1 , wherein applying the neighborhood characterization comprises sending sponsored content to one or more users of the social networking system that belong to a particular subregion, based on the success of the sponsored content in one or more different subregions with a similar degree of ubiquity of the tags across the subregions in the regions. 6 . The method of claim 1 , wherein identifying one or more of the tags that are common to multiple ones of the subregions across the different regions comprises identifying tags that occur above a pre-determined rate among a plurality of users located within a single subregion. 7 . The method of claim 1 , further comprising: generating a visual representation of the neighborhood characterization. 8 . The method of claim 1 , wherein the neighborhood characterization comprises a composite characterization of two or more different topics. 9 . The method of claim 1 , further comprising generating one or more additional neighborhood characterizations based on the identified tags from one or more additional neighborhoods; and quantifying the similarity between tags of different neighborhoods. 10 . One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive postings submitted by one or more users of a social-networking system, wherein a posting comprises location data and one or more tags; for each of the postings, based on the location data, identify one of a plurality of regions and one of a plurality of subregions of the regions; determine a distribution of the tags according to two data dimensions, a first one of the data dimensions comprising a degree of ubiquity of the tags across the regions, a second one of the data dimensions comprising a degree of ubiquity of the tags across the subregions in the regions; based on the distribution, identify one or more of the tags that are common to multiple ones of the subregions across the different regions; generate a neighborhood characterization based on the identified tags; and apply the neighborhood characterization. 11 . The media of claim 10 , wherein a region comprises a state, province, county, or a city, and wherein a subregion comprises a neighborhood. 12 . The media of claim 10 , wherein the software is further operable when executed to generate a visual representation of the distribution of the tags. 13 . The media of claim 10 , wherein generating a neighborhood characterization based on the identified tags comprises applying natural language processing to content associated with the postings to generate the neighborhood characterization. 14 . The media of claim 10 , wherein applying the neighborhood characterization comprises sending sponsored content to one or more users of the social networking system that belong to a particular subregion, based on the success of the sponsored content in one or more different subregions with a similar degree of ubiquity of the tags across the subregions in the regions. 15 . The media of claim 10 , wherein identifying one or more of the tags that are common to multiple ones of the subregions across the different regions comprises identifying tags that occur above a pre-determined rate among a plurality of users located within a single subregion. 16 . The media of claim 10 , wherein the software is further operable when executed to generate a visual representation of the neighborhood characterization. 17 . The media of claim 10 , wherein the neighborhood characterization comprises a composite characterization of two or more different topics. 18 . The media of claim 10 , wherein the software is further operable when executed to generate one or more additional neighborhood characterizations based on the identified tags from one or more additional neighborhoods; and quantify the similarity between tags of different neighborhoods. 19 . A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to: receive postings submitted by one or more users of a social-networking system, wherein a posting comprises location data and one or more tags; for each of the postings, based on the location data, identify one of a plurality of regions and one of a plurality of subregions of the regions; determine a distribution of the tags according to two data dimensions, a first one of the data dimensions comprising a degree of ubiquity of the tags across the regions, a second one of the data dimensions comprising a degree of ubiquity of the tags across the subregions in the regions; based on the distribution, identify one or more of the tags that are common to multiple ones of the subregions across the different regions; generate a neighborhood characterization based on the identified tags; and apply the neighborhood characterization. 20 . The system of claim 19 , wherein the processors are further operable when executing the instructions to generate one or more additional neighborhood characterizations based on the identified tags from one or more additional neighborhoods; and quantify the similarity between tags of different neighborhoods.

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What does patent US2017193073A1 cover?
In one embodiment, a method includes a computing device receiving postings from users of an online social networking system. A postings may include location data along with one or more tags that may describe the content of the posting. The computing device may identify regions and subregions from which the postings originated, and may determine a distribution of the tags according to two data d…
Who is the assignee on this patent?
Facebook Inc
What technology area does this patent fall under?
Primary CPC classification H04L67/306. Mapped technology areas include Electricity.
When was this patent published?
Publication date Thu Jul 06 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).