Quotations-modules on online social networks
First Claim
1. A method comprising, by one or more computing devices:
- accessing, by the one or more computing devices, a plurality of communications authored by one or more users of an online social network, each communication being associated with a particular content item and comprising a text of the communication;
extracting, for each of the plurality of communications, one or more quotations from the text of the communication;
determining, for each extracted quotation, one or more partitions of the quotation;
grouping, by the one or more computing devices, the extracted quotations into one or more clusters based on a respective degree of similarity among their respective one or more partitions;
calculating, by the one or more computing devices, a cluster-score for each cluster based on a frequency of occurrence of one or more partitions of one or more quotations in the cluster in communications associated with the particular content item;
calculating, by the one or more computing devices, a quotation-score for each quotation in a cluster having a cluster-score greater than a threshold cluster-score, wherein the quotation-score is calculated based on the following expression;
q Σ
i=0n (α
×
similarity metric), wherein q is a count of occurrences of quotations that are exact matches and α
is a respective count of occurrences of quotations that are not exact matches in a total set of unique extracted quotations defined from i=0 to i=n, and wherein the similarity metric is a measure of a degree of similarity between a quotation that is an exact match and the respective quotation that is not an exact match; and
generating, by the one or more computing devices, a quotations-module comprising one or more representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score, and each representative quotation having a quotation-score greater than a threshold quotation-score.
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Accused Products
Abstract
In one embodiment, a method includes accessing a plurality of communications, each communication being associated with a particular content item and including a text of the communication; extracting, for each of the communications, quotations from the text of the communication; determining, for each extracted quotation, partitions of the quotation; grouping the extracted quotations into clusters based on a respective degree of similarity among their respective partitions; calculating a cluster-score for each cluster based on a frequency of occurrence of partitions of quotations in the cluster in the communications; and generating a quotations-module comprising representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score.
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Citations
20 Claims
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1. A method comprising, by one or more computing devices:
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accessing, by the one or more computing devices, a plurality of communications authored by one or more users of an online social network, each communication being associated with a particular content item and comprising a text of the communication; extracting, for each of the plurality of communications, one or more quotations from the text of the communication; determining, for each extracted quotation, one or more partitions of the quotation; grouping, by the one or more computing devices, the extracted quotations into one or more clusters based on a respective degree of similarity among their respective one or more partitions; calculating, by the one or more computing devices, a cluster-score for each cluster based on a frequency of occurrence of one or more partitions of one or more quotations in the cluster in communications associated with the particular content item; calculating, by the one or more computing devices, a quotation-score for each quotation in a cluster having a cluster-score greater than a threshold cluster-score, wherein the quotation-score is calculated based on the following expression; q Σ
i=0n (α
×
similarity metric), wherein q is a count of occurrences of quotations that are exact matches and α
is a respective count of occurrences of quotations that are not exact matches in a total set of unique extracted quotations defined from i=0 to i=n, and wherein the similarity metric is a measure of a degree of similarity between a quotation that is an exact match and the respective quotation that is not an exact match; andgenerating, by the one or more computing devices, a quotations-module comprising one or more representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score, and each representative quotation having a quotation-score greater than a threshold quotation-score. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
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access a plurality of communications authored by one or more users of an online social network, each communication being associated with a particular content item and comprising a text of the communication; extract, for each of the plurality of communications, one or more quotations from the text of the communication; determine, for each extracted quotation, one or more partitions of the quotation; group the extracted quotations into one or more clusters based on a respective degree of similarity among their respective one or more partitions; calculate a cluster-score for each cluster based on a frequency of occurrence of one or more partitions of one or more quotations in the cluster in communications associated with the particular content item; calculate a quotation-score for each quotation in a cluster having a cluster-score greater than a threshold cluster-score, wherein the quotation-score is calculated based on the following expression; q Σ
i=0n (α
×
similarity metric), wherein q is a count of occurrences of quotations that are exact matches and α
is a respective count of occurrences of quotations that are not exact matches in a total set of unique extracted quotations defined from i=0 to i=n, and wherein the similarity metric is a measure of a degree of similarity between a quotation that is an exact match and the respective quotation that is not an exact match; andgenerate a quotations-module comprising one or more representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score, and each representative quotation having a quotation-score greater than a threshold quotation-score.
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20. A system comprising:
- one or more processors; and
a non-transitory memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to;access a plurality of communications authored by one or more users of an online social network, each communication being associated with a particular content item and comprising a text of the communication; extract, for each of the plurality of communications, one or more quotations from the text of the communication; determine, for each extracted quotation, one or more partitions of the quotation; group the extracted quotations into one or more clusters based on a respective degree of similarity among their respective one or more partitions; calculate a cluster-score for each cluster based on a frequency of occurrence of one or more partitions of one or more quotations in the cluster in communications associated with the particular content item; calculate a quotation-score for each quotation in a cluster having a cluster-score greater than a threshold cluster-score, wherein the quotation-score is calculated based on the following expression; q Σ
i=0n (α
×
similarity metric), wherein q is a count of occurrences of quotations that are exact matches and α
is a respective count of occurrences of quotations that are not exact matches in a total set of unique extracted quotations defined from i=0 to i=n, and wherein the similarity metric is a measure of a degree of similarity between a quotation that is an exact match and the respective quotation that is not an exact match; andgenerate a quotations-module comprising one or more representative quotations, each representative quotation being a quotation from a cluster having a cluster-score greater than a threshold cluster-score, and each representative quotation having a quotation-score greater than a threshold quotation-score.
- one or more processors; and
Specification