System and method for computing critical data of an entity using cognitive analysis of emergent data

A system, interfacing with multiple communications channels for retrieving data from multiple data sources associated with multiple entities, for computing critical data of the multiple entities, the system executing instructions stored in a memory via a processor, the system comprising:

• an inference engine, executed by one or more processors, in communication with the processor and configured to:
• assign an element, from a set of predetermined elements, to each sentence of a first dataset associated with an entity of an industry type, the predetermined elements being characteristic of reputation of entities of various industries;
• categorize features determined from the sentences of the first dataset into one or more groups, wherein each group represents related features corresponding to each assigned element;
• match features of a new dataset of a different entity of the said industry type with the grouped features of the said industry type for allotting groups to the matched features similar to the groups of the grouped features;
• apply one or more classification rules to the matched features to generate metadata representing instructions for assigning an element to each sentence of the new dataset, the classification rules being created based on the grouped features and the assigned elements;
• assign the element to each sentence of the new dataset based on the applied classification rules, thereby the element assigned to each sentence of the new dataset of the different entity of the said industry type is same as the element assigned to each sentence of the first dataset of the said entity of the said industry type;
• and
• generate a reputation score for the said entities, wherein the reputation score is generated by determining positive and negative sentiments in the first and the new dataset,
• wherein the assigning of element to the first dataset and the feature grouping steps are repeated for datasets associated with entities of different industry types for creating a taxonomy for each of the different industry types, and
• wherein the inference engine comprises a labelling unit in communication with the processor and configured to:
• assign the element to each sentence of a first dataset fetched from a data storage based on cognitive analysis capability developed by the system using pre-existing dataset associated with entities of different industry types collected over a period of time;
• and
• update pre-existing data with content of the first dataset and the new dataset.

A computer program product comprising:

• a non-transitory computer-readable medium having computer-readable program code stored thereon, the computer-readable program code comprising instructions that, when executed by a processor, cause the processor to:
• a. assign an element to each sentence of a first dataset fetched from a data storage, the sentence associated with an entity of an industry type, the element being assigned to each sentence from a set of predetermined elements, the predetermined elements being characteristic of reputation of entities of various industries, wherein the element is assigned to each sentence of the first dataset based on cognitive analysis capability developed by the tool using pre-existing dataset associated with entities of different industry types collected over a period of time;
• b. categorize features of the first dataset into one or more groups, wherein each group represents related features corresponding to each assigned element;
• c. match the features of the new dataset of a different entity of the said industry type with the grouped features of the said industry type to allot groups to the matched features similar to the groups of the grouped features;
• d. apply one or more classification rules on the new dataset to the matched features to generate metadata representing instructions for assigning an element to each sentence of the new dataset, wherein the one or more classification rules are created based on the assigned elements and the grouped features;
• e. generate metadata representing instructions for assigning an element to each sentence of the new dataset of the different entity of the said industry type based on the grouping of the matched features;
• f. assign an element to each sentence of the new dataset based on the metadata, wherein the element assigned to each sentence of the new dataset of the different entity of the said industry type is same as the element assigned to each sentence of the first dataset of the said entity of the said industry type;
• g. analyze the elements assigned to the first dataset and the new dataset to identify a sentiment associated with the said entities of the said industry type, wherein the sentiment is identified by determining sentences from the first and the new dataset as representing a positive sentiment or a negative sentiment;
• and
• h. generate a reputation score for the said entities based on the identified sentiments,
• wherein steps a and b are repeated for datasets associated with entities of different industry types for creating a taxonomy for each of the different industry types, and
• wherein the pre-existing data in the tool is undated with content of the first dataset and the new dataset.