Abstract: A system, method and computer program product for scalable, rule-based processing, including an automaton builder for constructing automatons corresponding to trigger rules and word lists that are employed by the trigger rules, and a rule evaluator for evaluating any of the trigger rules with respect to an input document by selecting any of the automatons to evaluate a given one of the trigger rules, parsing the input document using the selected automatons, determining whether conditions of the given trigger rule are met, and identifying any actions that are associated with the given trigger rule.

Abstract: Facilitating the searching of structured documents by identifying multiple element paths corresponding to multiple elements included in multiple structured documents, and for each of the element paths providing, for inclusion in a first searchable data structure, the element path exclusive of a value of the element corresponding to the element path and exclusive of an identifier of the structured document including the element corresponding to the element path, and providing, for inclusion in a second searchable data structure, the element path in association with a value of the element corresponding to the element path and in association with an identifier of the structured document including the element corresponding to the element path.

Abstract: Machines, systems and methods for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of the representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events.

Abstract: Machines, systems and methods for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of the representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events.

Abstract: Facilitating the searching of structured documents by identifying multiple element paths corresponding to multiple elements included in multiple structured documents, and for each of the element paths providing, for inclusion in a first searchable data structure, the element path exclusive of a value of the element corresponding to the element path and exclusive of an identifier of the structured document including the element corresponding to the element path, and providing, for inclusion in a second searchable data structure, the element path in association with a value of the element corresponding to the element path and in association with an identifier of the structured document including the element corresponding to the element path.

Abstract: A system, method and computer program product for scalable, rule-based processing, including an automaton builder for constructing automatons corresponding to trigger rules and word lists that are employed by the trigger rules, and a rule evaluator for evaluating any of the trigger rules with respect to an input document by selecting any of the automatons to evaluate a given one of the trigger rules, parsing the input document using the selected automatons, determining whether conditions of the given trigger rule are met, and identifying any actions that are associated with the given trigger rule.

Abstract: Machines, systems and methods for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of the representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events.

Abstract: Machines, systems and methods for maintaining a representative data set in a document classification system, the method comprising: including an initial set of seed representative data in a representative data set (RDS) implemented for a knowledge base (KB), wherein the KB is trained to classify documents provided to a document classification system based on analysis of the representative documents included in the RDS and a set of rules, wherein the seed representative data includes a balanced number of representative data across a plurality of classes; updating the RDS by adding or removing representative data from the RDS based on feedback received about accuracy of classification of one or more documents by the classification system; and retraining the KB, wherein the retraining is performed based on occurrence of one or more events.

Abstract: Facilitating the searching of structured documents by identifying multiple element paths corresponding to multiple elements included in multiple structured documents, and for each of the element paths providing, for inclusion in a first searchable data structure, the element path exclusive of a value of the element corresponding to the element path and exclusive of an identifier of the structured document including the element corresponding to the element path, and providing, for inclusion in a second searchable data structure, the element path in association with a value of the element corresponding to the element path and in association with an identifier of the structured document including the element corresponding to the element path.

Abstract: Facilitating the searching of structured documents by identifying multiple element paths corresponding to multiple elements included in multiple structured documents, and for each of the element paths providing, for inclusion in a first searchable data structure, the element path exclusive of a value of the element corresponding to the element path and exclusive of an identifier of the structured document including the element corresponding to the element path, and providing, for inclusion in a second searchable data structure, the element path in association with a value of the element corresponding to the element path and in association with an identifier of the structured document including the element corresponding to the element path.

Abstract: A system, method and computer program product for scalable, rule-based processing, including an automaton builder for constructing automatons corresponding to trigger rules and word lists that are employed by the trigger rules, and a rule evaluator for evaluating any of the trigger rules with respect to an input document by selecting any of the automatons to evaluate a given one of the trigger rules, parsing the input document using the selected automatons, determining whether conditions of the given trigger rule are met, and identifying any actions that are associated with the given trigger rule.

Abstract: A system, method and computer program product for scalable, rule-based processing, including an automaton builder for constructing automatons corresponding to trigger rules and word lists that are employed by the trigger rules, and a rule evaluator for evaluating any of the trigger rules with respect to an input document by selecting any of the automatons to evaluate a given one of the trigger rules, parsing the input document using the selected automatons, determining whether conditions of the given trigger rule are met, and identifying any actions that are associated with the given trigger rule.