Abstract: System and method for computing critical data of multiple entities is provided. Elements, from a set of predetermined elements, are assigned to sentences of a first dataset associated with an entity of an industry type. Predetermined elements characterize reputation of entities of various industries. Features determined from sentences of first dataset are categorized into groups. Features of a new dataset of a different entity of said industry type are matched with grouped features and same groups are allotted thereto. Classification rules are applied on matched features. Elements are assigned to sentences of new dataset based on allotted groups, which elements are same as those assigned to first dataset. Reputation scores are generated for said entities by determining positive and negative sentiments from the first and new dataset. Steps of assigning elements and grouping are repeated for datasets associated with entities of different industry types for creating a taxonomy for them.

Abstract: System and method for computing critical data of multiple entities is provided. Elements, from a set of predetermined elements, are assigned to sentences of a first dataset associated with an entity of an industry type. Predetermined elements characterize reputation of entities of various industries. Features determined from sentences of first dataset are categorized into groups. Features of a new dataset of a different entity of said industry type are matched with grouped features and same groups are allotted thereto. Classification rules are applied on matched features. Elements are assigned to sentences of new dataset based on allotted groups, which elements are same as those assigned to first dataset. Reputation scores are generated for said entities by determining positive and negative sentiments from the first and new dataset. Steps of assigning elements and grouping are repeated for datasets associated with entities of different industry types for creating a taxonomy for them.