Method for refining cognitive insights using travel-related cognitive graph vectors
A method, system and computer-usable medium are disclosed for using travel-related cognitive graph vectors.
1. A cognitive inference and learning system for determining cognitive insights using cognitive graph vectors comprising:
a data store storing a cognitive graph including travel-related data from a plurality of data sources graph comprising a set of nodes and links between the nodes that represent travel-related knowledge;
a processor; and
a non-transitory computer readable medium including instructions for:
associating a first subset of the set of nodes and links of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors, wherein the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus, wherein a specificity of the first cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each first cognitive graph vector index corresponding to a first travel-related attribute comprising one or more of who, how, why, where, when or what;
associating a second subset of the set of nodes and links of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of cognitive graph vectors, wherein the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus, wherein a specificity of the second cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each second cognitive graph vector index corresponding to a second travel-related attribute comprising one or more of who, how, why, where, when or what;
receiving a user query;
generating a first cognitive graph vector parameter for the first travel-related cognitive graph vector based on the user query;
generating an initial travel-related cognitive insight from the cognitive graph based on the first cognitive graph vector parameter;
defining a second cognitive graph vector parameter for the second travel-related cognitive vector based on the initial travel-related cognitive insight;
generating a graph query based on the user query, the first cognitive graph vector parameter and the second cognitive graph vector parameter;
querying a third subset of the set of nodes and links of the cognitive graph defined by the first cognitive graph vector and the second cognitive graph vector with the graph query to generate second travel-related cognitive insights; and
returning the second travel-related cognitive insights in response to the user query.
2. The cognitive inference and learning system of claim 1 , wherein the user query is evaluated to determine that the first cognitive graph vector parameter is to be determined for first travel-related cognitive graph vector.
3. The cognitive inference and learning system of claim 1 , wherein each of the first cognitive graph vector and second cognitive graph vector are associated with a predetermined subset of the set of nodes and links of the cognitive graph.
4. The cognitive inference and learning system of claim 1 , wherein the third subset of the set of nodes and links of the cognitive graph limits the first subset of nodes and links of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices and limits the second subset of nodes and links of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
5. The cognitive inference and learning system of claim 4 , wherein:
at least some of the first cognitive graph vector indices or second cognitive graph vector indices are different magnitudes.
6. The cognitive inference and learning system of claim 5 , wherein the first cognitive graph vector indices and second cognitive graph vector indices are associated with pre-determined travel related attributes.
7. A non-transitory computer readable medium storing instructions for generating cognitive insights using cognitive graph vectors by:
storing a cognitive graph including travel-related data from a plurality of data sources graph comprising a set of nodes and links between the nodes that represent travel-related knowledge;
associating a first subset of the set of nodes and links of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors, wherein the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus, wherein a specificity of the first cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each first cognitive graph vector index corresponding to a first travel-related attribute comprising one or more of who, how, why, where, when or what;
associating a second subset of the set of nodes and links of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of cognitive graph vectors, wherein the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus, wherein a specificity of the second cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each second cognitive graph vector index corresponding to a second travel-related attribute comprising one or more of who, how, why, where, when or what;
receiving a user query;
generating a first cognitive graph vector parameter for the first travel-related cognitive graph vector based on the user query;
generating an initial travel-related cognitive insight from the cognitive graph based on the first cognitive graph vector parameter;
defining a second cognitive graph vector parameter for the second travel-related cognitive vector based on the initial travel-related cognitive insight;
generating a graph query based on the user query, the first cognitive graph vector parameter and the second cognitive graph vector parameter;
querying a third subset of the set of nodes and links of the cognitive graph defined by the first cognitive graph vector and the second cognitive graph vector with the graph query to generate second travel-related cognitive insights; and
returning the second travel-related cognitive insights in response to the user query.
8. The non-transitory computer readable medium of claim 7 , wherein the user query is evaluated to determine that the first cognitive graph vector parameter is to be determined for first travel-related cognitive graph vector.
9. The non-transitory computer readable medium of claim 7 , wherein each of the first cognitive graph vector and second cognitive graph vector are associated with a predetermined subset of the set of nodes and links of the cognitive graph.
10. The non-transitory computer readable medium of claim 7 , wherein the third subset of the set of nodes and links of the cognitive graph limits the first subset of nodes and links of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices and limits the second subset of nodes and links of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
11. The non-transitory computer readable medium of claim 10 , wherein:
at least some of the first cognitive graph vector indices or second cognitive graph vector indices are different magnitudes.
12. The non-transitory computer readable medium of claim 11 , wherein the first cognitive graph vector indices and second cognitive graph vector indices are associated with pre-determined travel related attributes.
13. A method for generating cognitive insights using cognitive graph vectors, comprising:
storing a cognitive graph including travel-related data from a plurality of data sources graph comprising a set of nodes and links between the nodes that represent travel-related knowledge;
associating a first subset of the set of nodes and links of the travel-related data within the cognitive graph with a first travel-related cognitive graph vector of a plurality of travel-related cognitive graph vectors, wherein the first travel-related cognitive graph vector comprises a plurality of first cognitive graph vector indices extending along the first travel-related cognitive graph vector away from a cognitive graph nexus, wherein a specificity of the first cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each first cognitive graph vector index corresponding to a first travel-related attribute comprising one or more of who, how, why, where, when or what;
associating a second subset of the set of nodes and links of the travel-related data within the cognitive graph with a second travel-related cognitive graph vector of the plurality of cognitive graph vectors, wherein the second travel-related cognitive graph vector comprises a plurality of second cognitive graph vector indices extending along the second travel-related cognitive graph vector away from the cognitive graph nexus, wherein a specificity of the second cognitive graph vector indices increases as they become more proximate to the cognitive graph nexus and each second cognitive graph vector index corresponding to a second travel-related attribute comprising one or more of who, how, why, where, when or what;
receiving a user query;
generating a first cognitive graph vector parameter for the first travel-related cognitive graph vector based on the user query;
generating an initial travel-related cognitive insight from the cognitive graph based on the first cognitive graph vector parameter;
defining a second cognitive graph vector parameter for the second travel-related cognitive vector based on the initial travel-related cognitive insight;
generating a graph query based on the user query, the first cognitive graph vector parameter and the second cognitive graph vector parameter;
querying a third subset of the set of nodes and links of the cognitive graph defined by the first cognitive graph vector and the second cognitive graph vector with the graph query to generate second travel-related cognitive insights; and
returning the second travel-related cognitive insights in response to the user query.
14. The method of claim 13 , wherein the user query is evaluated to determine that the first cognitive graph vector parameter is to be determined for first travel-related cognitive graph vector.
15. The method of claim 13 , wherein each of the first cognitive graph vector and second cognitive graph vector are associated with a predetermined subset of the set of nodes and links of the cognitive graph.
16. The method of claim 13 , wherein the third subset of the set of nodes and links of the cognitive graph limits the first subset of nodes and links of travel-related data to travel-related data within a first certain index of the plurality of first cognitive graph vector indices and limits the second subset of nodes and links of travel-related data to travel-related data within a second certain index of the second cognitive graph vector indices.
17. The method of claim 16 , wherein:
at least some of the first cognitive graph vector indices or second cognitive graph vector indices are different magnitudes.
18. The method of claim 17 , wherein the first cognitive graph vector indices and second cognitive graph vector indices are associated with pre-determined travel related attributes.