A computer-implemented method for collating relevant information to assist a user in a decision-making process is provided. The method includes receiving, from a plurality of data sources, a plurality of pieces of data including contextual features, and populating at least one contextual model with the plurality of pieces of data. The at least one contextual model groups pieces of data based at least in part on the contextual features. The method also includes calculating one or more contextual relationships based on the at least one contextual model, and determining one or more pieces of data of the at least one contextual model to provide to a user based on the one or more contextual relationships and one or more decision making rules.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method for collating relevant information to assist a user in a decision-making process, the method implemented using a contextual information collating (CIC) server system in communication with a memory, the method comprising: receiving, from a plurality of data sources, a plurality of pieces of data including contextual features; populating at least one contextual model with the plurality of pieces of data, wherein the at least one contextual model groups pieces of data based at least in part on the contextual features; calculating, by the CIC server system, one or more contextual relationships based on the at least one contextual model; and determining, by the CIC server system, one or more pieces of data of the at least one contextual model to provide to a user based on the one or more contextual relationships and one or more decision making rules. 2. A method in accordance with claim 1, further comprising: associating a confidence score with at least one piece of data of the plurality of pieces of data; and filtering the at least one contextual model based on the confidence score associated with the at least one piece of data. 3. A method in accordance with claim 2, further comprising receiving the confidence score from the user. 4. A method in accordance with claim 3, wherein the user is a first user and the confidence score is a first confidence score, and further comprising: receiving a second confidence score from a second user; filtering the at least one contextual model based on the first confidence score for the first user; and filtering the at least one contextual model based on the second confidence score for the second user. 5. A method in accordance with claim 1, further comprising generating at least one higher level contextual model based on the at least one contextual model, wherein the at least one higher level contextual model further limits pieces of data based at least in part on the contextual features. 6. A method in accordance with claim 5, wherein data for the at least one higher level contextual model is received directly from the at least one contextual model. 7. A method in accordance with claim 1, further comprising providing, to a user, the one or more determined pieces of data. 8. A method in accordance with claim 1, wherein determining one or more pieces of data further comprises: receiving, from a user, a selection of a decision to make; and determining the one or more decision making rules based on the selected decision. 9. A method in accordance with claim 1, wherein at least one of the one or more contextual relationships is a temporal spatial relationship. 10. A method in accordance with claim 1, wherein the plurality of pieces of data includes hard data and soft data. 11. A contextual information collating (CIC) server system used to collate relevant information to assist a user in a decision-making process, said CIC server system comprising a processor coupled to a memory device, said processor programmed to: receive, from a plurality of data sources, a plurality of pieces of data including contextual features; populate at least one contextual model with the plurality of pieces of data, wherein the at least one contextual model groups pieces of data based at least in part on the contextual features; calculate one or more contextual relationships based on the at least one contextual model; and determine one or more pieces of data of the at least one contextual model, which is provided to a user based on the one or more contextual relationships and one or more decision making rules. 12. The CIC server system of claim 11, wherein the at least one processor is further programmed to: associate a confidence score with at least one piece of data of the plurality of pieces of data; and filter the at least one contextual model based on the confidence score associated with the at least one piece of data. 13. The CIC server system of claim 12, wherein the at least one processor is further programmed to receive the confidence score from the user. 14. The CIC server system of claim 13, wherein the user is a first user and the confidence score is a first confidence score, and wherein the at least one processor is further programmed to: receive a second confidence score from a second user; filter the at least one contextual model based on the first confidence score for the first user; and filter the at least one contextual model based on the second confidence score for the second user. 15. The CIC server system of claim 11, wherein the at least one processor is further programmed to generate at least one higher level contextual model based on the at least one contextual model, wherein the at least one higher level contextual model further limits pieces of data based at least in part on the contextual features. 16. The CIC server system of claim 15, wherein data for the at least one higher level contextual model is received directly from the at least one contextual model. 17. The CIC server system of claim 11, wherein the at least one processor is further programmed to provide, to a user, the one or more determined pieces to data. 18. The CIC server system of claim 11, wherein the at least one processor is further programmed to: receive, from a user, a selection of a decision to make; and determine the one or more decision making rules based on the selected decision. 19. A method in accordance with claim 1, wherein the plurality of pieces of data includes hard data and soft data. 20. At least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the at least one processor to: receive, from a plurality of data sources, a plurality of pieces of data including contextual features; populate at least one contextual model with the plurality of pieces of data, wherein the at least one contextual model groups pieces of data based at least in part on the contextual features; calculate one or more contextual relationships based on the at least one contextual model; and determine one or more pieces of data of the at least one contextual model to provide to a user based on the one or more contextual relationships and one or more decision making rules.