Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Classifying an electronic document in a computer-based system is disclosed. For each classification instance in a plurality of classification instances, a confidence data indicating a degree of confidence that the electronic document is associated with that classification instance is determined. A classification, based on a first classification instance in the plurality of classification instances, is assigned without human intervention to the electronic document if the confidence data associated with the first classification instance exceeds a first threshold.

Abstract: Discloses a system for the automatic classification of electronic documents that are candidates to become an official record. A training data set of documents, each document having a pre-assigned records classification instance, is processed by a classification agent operating in training mode to establish a probabilistic relationship between each classification instance and the contents of a document. The training data set includes at least several documents per classification instance. A trained classification agent operating in evaluation or classification mode receives a candidate document and produces a result. A decision control table contains user specified contiguous result ranges to select one document processing action from a list of document processing actions based on the result produced by the trained classification agent.

Abstract: Discloses a system for the automatic classification of electronic documents that are candidates to become an official record. A training data set of documents, each document having a pre-assigned records classification instance, is processed by a classification agent operating in training mode to establish a probabilistic relationship between each classification instance and the contents of a document. The training data set includes at least several documents per classification instance. A trained classification agent operating in evaluation or classification mode receives a candidate document and produces a result. A decision control table contains user specified contiguous result ranges to select one document processing action from a list of document processing actions based on the result produced by the trained classification agent.

Abstract: Discloses a system for the automatic classification of electronic documents that are candidates to become an official record. A training data set of documents, each document having a pre-assigned records classification instance, is processed by a classification agent operating in training mode to establish a probabilistic relationship between each classification instance and the contents of a document. The training data set includes at least several documents per classification instance. A trained classification agent operating in evaluation or classification mode receives a candidate document and produces a result. A decision control table contains user specified contiguous result ranges to select one document processing action from a list of document processing actions based on the result produced by the trained classification agent.