System and method for generating personal vocabulary from network data
US-8990083-B1 · Mar 24, 2015 · US
US9280534B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9280534-B2 |
| Application number | US-201213681227-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 19, 2012 |
| Priority date | Nov 19, 2012 |
| Publication date | Mar 8, 2016 |
| Grant date | Mar 8, 2016 |
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Particular embodiments determine that a textual term is not associated with a known meaning. The textual term may be related to one or more users of the social-networking system. A determination is made as to whether the textual term should be added to a glossary. If so, then the textual term is added to the glossary. Information related to one or more textual terms in the glossary is provided to enhance auto-correction, provide predictive text input suggestions, or augment social graph data. Particular embodiments discover new textual terms by mining information, wherein the information was received from one or more users of the social-networking system, was generated for one or more users of the social-networking system, is marked as being associated with one or more users of the social-networking system, or includes an identifier for each of one or more users of the social-networking system.
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What is claimed is: 1. A method comprising: by one or more computer servers associated with a social-networking system, determining that a textual term is not associated with a known meaning, wherein the textual term is related to one or more users of the social-networking system, the user being associated with a user node in a social graph of the social-networking system, the social graph comprising: a plurality of nodes, the plurality of nodes comprising user nodes and concept nodes, wherein each user node corresponds to a user of the social-networking system; and a plurality of edges, wherein one or more edges connect two nodes, the one or more edges representing a relationship between the two nodes; by the one or more computer servers, determining that the textual term should be added to a social glossary; by the one or more computer servers, adding the textual term to the social glossary; by the one or more computer servers, adding to the social graph a new element representing the textual term, wherein the new element comprises: a new concept node, wherein the textual term is a noun, a new edge, wherein the textual term is a verb, or a new attribute for the user node, wherein the textual term is an adjective; and by the one or more computer servers, providing information related to one or more textual terms in the social glossary. 2. The method of claim 1 , further comprising: discovering new textual terms by mining information, wherein the information was received from one or more users of the social-networking system, was generated for one or more users of the social-networking system, is marked as being associated with one or more users of the social-networking system, or includes an identifier for each of one or more users of the social-networking system. 3. The method of claim 1 , wherein the determination that the textual term is not associated with a known meaning is based on one or more dictionaries, glossaries, logs, or indices. 4. The method of claim 1 , wherein the determining that the textual term is not associated with a known meaning is performed in relation to one or more languages associated with the user, one or more languages associated with social graph contacts of the user, one or more languages associated with content generated or consumed by the user, or any language. 5. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary comprises determining that the textual term does not represent an error, the determination based on a user override of an auto-correction of the textual term, an addition of the textual term to a personal social glossary of the user, or a set of common spelling errors. 6. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary is based on usage statistics for the textual term based on usage by: users of the social-networking system, users having a relationship with the user according to the social graph, users using the same language as the user, users located within the same geographic area as the user, users sharing a demographic category with the user, or users sharing similar profile attributes with the user. 7. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary is based on a usage context of the textual term. 8. The method of claim 1 , wherein the determining that the textual term should be added to the social glossary is based on a poll of users. 9. The method of claim 8 , wherein the poll is limited to: users of the social-networking system, users having a relationship with the user according to the social graph, users using the same language as the user, users sharing a demographic category with the user, or users sharing similar profile attributes with the user. 10. The method of claim 1 , further comprising: storing the textual term in association with one or more users, groups, locales, user attributes, or usage contexts. 11. The method of claim 1 , wherein the providing information related to one or more textual terms in the social glossary comprises: providing auto-correction of entered text based on the textual terms, providing predictive text input suggestions based on the textual terms, providing an interface for third-party systems to access the social glossary, or providing information to enhance the social graph. 12. The method of claim 11 , wherein the adding to the social graph the new element representing the textual term comprises: determining that the textual term comprises a reference to a person, an entity, content, an action, or anything else represented in the social graph by a node or edge. 13. The method of claim 1 , further comprising: removing information associated with obsolete textual terms from the social glossary. 14. The method of claim 1 , further comprising: providing an interface to manage the social glossary, the interface including functionality to add, remove, edit, and adjust properties of textual terms in the social glossary. 15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: determine that a textual term is not associated with a known meaning, wherein the textual term is related to one or more users of a social-networking system, the user being associated with a user node in a social graph of the social-networking system, the social graph comprising: a plurality of nodes, the plurality of nodes comprising user nodes and concept nodes, wherein each user node corresponds to a user of the social-networking system; and a plurality of edges, wherein one or more edges connect two nodes, the one or more edges representing a relationship between the two nodes; determine that the textual term should be added to a social glossary; add the textual term to the social glossary; add to the social graph a new element representing the textual term, wherein the new element comprises: a new concept node, wherein the textual term is a noun, a new edge, wherein the textual term is a verb, or a new attribute for the user node, wherein the textual term is an adjective; and provide information related to one or more textual terms in the social glossary. 16. The media of claim 15 , wherein the software is further operable to: discover new textual terms by mining information, wherein the information was received from one or more users of the social-networking system, was generated for one or more users of the social-networking system, is marked as being associated with one or more users of the social-networking system, or includes an identifier for each of one or more users of the social-networking system. 17. The media of claim 15 , wherein the determination that the textual term should be added to the social glossary is based on usage statistics for the textual term based on usage by: users of the social-networking system, users having a relationship with the user according to the social graph, users using the same language as the user, users located within the same geographic area as the user, users sharing a demographic category with the user, or users sharing similar profile attributes with the user. 18. A system, comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: determine that a textual term is not associated with a known meaning, wherein the textual term is related to one
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