Predictive intelligent softbots on the cloud
First Claim
1. A method comprising:
- receiving, using one or more processors, a plurality of time-based documents;
receiving, by a Software as a Service cloud-based server, a user query including a time period of interest defining a subset of the plurality of time-based documents from which to generate a prediction;
determining to activate a plurality of cloud-based software agents, which execute on a plurality of remote computational devices geographically distributed across world geography, based on a plurality of entities associated with the user query, wherein each of the plurality of cloud-based software agents is dedicated to a single entity within the plurality of entities associated with the user query;
classifying, by executing the plurality of cloud-based software agents on the plurality of remote computational devices, the subset of the plurality of time-based documents into a plurality of classes for the plurality of entities, wherein the plurality of cloud-based software agents intercommunicate using distributed processing; and
generating, by executing the plurality of cloud-based software agents on the plurality of remote computational devices, using at least one machine learning method, the prediction based on the subset of the plurality of time-based documents for at least one of a plurality of categories.
9 Assignments
0 Petitions
Accused Products
Abstract
A system and method for generating a prediction are disclosed. In one embodiment, the method includes receiving a plurality of time-based documents; receiving a user query including a time period of interest defining a subset of the time-based documents from which to generate a prediction; and a plurality of cloud-based software agents classifying the subset of the plurality of time-based documents into a plurality of classes for the plurality entities, wherein the plurality of cloud-based software agents intercommunicate using distributed processing, wherein each of the plurality of cloud-based software agents is dedicated to one of the entities in the plurality of entities; and generating, using at least one machine learning method, the prediction based on the subset of the plurality of time-based documents for at least one of a plurality of categories. However, other embodiments are disclosed.
-
Citations
69 Claims
-
1. A method comprising:
-
receiving, using one or more processors, a plurality of time-based documents; receiving, by a Software as a Service cloud-based server, a user query including a time period of interest defining a subset of the plurality of time-based documents from which to generate a prediction; determining to activate a plurality of cloud-based software agents, which execute on a plurality of remote computational devices geographically distributed across world geography, based on a plurality of entities associated with the user query, wherein each of the plurality of cloud-based software agents is dedicated to a single entity within the plurality of entities associated with the user query; classifying, by executing the plurality of cloud-based software agents on the plurality of remote computational devices, the subset of the plurality of time-based documents into a plurality of classes for the plurality of entities, wherein the plurality of cloud-based software agents intercommunicate using distributed processing; and generating, by executing the plurality of cloud-based software agents on the plurality of remote computational devices, using at least one machine learning method, the prediction based on the subset of the plurality of time-based documents for at least one of a plurality of categories. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
-
13. A method comprising:
-
receiving, using one or more processors, a time-based query from a user; determining a classification criterion, a relationship criterion, and a time period of interest from the time-based query; obtaining at least one second classification criterion, at least one second relationship criterion, a plurality of concepts, and a plurality of entities from a knowledge base; classifying a plurality of documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed machine learning method; extracting the plurality of entities for the relationship criterion, the at least one second relationship criterion from a plurality of classified documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed processing; generating a plurality of data representations between the relationship criterion and said plurality of entities based on said classification criterion and the time-based query using the plurality of classified documents; and applying a distributed processing method to manipulate said plurality of data representations for generating a visualization of a prediction responsive to the time-based query, wherein the prediction captures a combined influence existing between the classification criterion, the at least one second classification criterion, the relationship criterion, and the at least one second relationship criterion. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23)
-
-
24. A system comprising;
-
a processing device implementing a Software as a Service cloud-based server for receiving a user query including a time period of interest defining a subset of a plurality of received time-based documents from which to generate a prediction; and a plurality of remote computational devices geographically distributed across world geography, the plurality of remote computational devices implementing a plurality of cloud-based software agents activated based on a plurality of entities associated with the user query, wherein each of the plurality of cloud-based software agents is dedicated to a single entity within the plurality of entities associated with the user query, the plurality of cloud-based software agents for classifying the subset of the plurality of time-based documents into a plurality of classes for the plurality of entities, wherein the plurality of cloud-based software agents intercommunicate using distributed processing, the plurality of cloud-based software agents generating, using at least one machine learning method, the prediction based on the subset of the plurality of time-based documents for at least one of a plurality of categories. - View Dependent Claims (25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35)
-
-
36. A system comprising;
-
a memory; and a processor operatively coupled to the memory, the processor configured to perform the steps of; receiving a time-based query from a user; determining a classification criterion, a relationship criterion, and a time period of interest from the time-based query; obtaining at least one second classification criterion, at least one second relationship criterion, a plurality of concepts and a plurality of entities from a knowledge base; classifying a plurality of documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed machine learning method; extracting the plurality of entities for the relationship criterion, the at least one second relationship criterion from a plurality of classified documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed processing; generating a plurality of data representations between the relationship criterion and said plurality of entities based on said classification criterion and the time-based query using the plurality of classified documents; and applying a distributed processing method to manipulate said plurality of data representations for generating a visualization of a prediction responsive to the time-based query, wherein the prediction captures a combined influence existing between the classification criterion, the at least one second classification criterion, the relationship criterion, and the at least one second relationship criterion. - View Dependent Claims (37, 38, 39, 40, 41, 42, 43, 44, 45, 46)
-
-
47. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, performs steps comprising:
-
receiving a plurality of time-based documents; receiving a user query including a time period of interest defining a subset of the plurality of time-based documents from which to generate a prediction; determining to activate a plurality of cloud-based software agents, which execute on a plurality of remote computational devices geographically distributed across world geography, based on a plurality of entities associated with the user query, wherein each of the plurality of cloud-based software agents is dedicated to a single entity within the plurality of entities associated with the user query; classifying, by executing the plurality of cloud-based software agents, the subset of the plurality of time-based documents into a plurality of classes for the plurality of entities, wherein the plurality of cloud-based software agents intercommunicate using distributed processing; and generating, by executing the plurality of cloud-based software agents on the plurality of remote computational devices, using at least one machine learning method, the prediction based on the subset of the plurality of time-based documents for at least one of a plurality of categories. - View Dependent Claims (48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58)
-
-
59. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, performs steps comprising:
-
receiving a time-based query from a user; determining a classification criterion, a relationship criterion, and a time period of interest from the time-based query; obtaining at least one second classification criterion, at least one second relationship criterion, a plurality of concepts, and a plurality of entities from a knowledge base; classifying a plurality of documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed machine learning method; extracting the plurality of entities for the relationship criterion, the at least one second relationship criterion from a plurality of classified documents based on the classification criterion, the at least one second classification criterion, and the time-based query using a distributed processing; generating a plurality of data representations between the relationship criterion and said plurality of entities based on said classification criterion and the time-based query using the plurality of classified documents; and applying a distributed processing method to manipulate said plurality of data representations for generating a visualization of a prediction responsive to the time-based query, wherein the prediction captures a combined influence existing between the classification criterion, the at least one second classification criterion, the relationship criterion, and the at least one second relationship criterion. - View Dependent Claims (60, 61, 62, 63, 64, 65, 66, 67, 68, 69)
-
Specification