Abstract: A system and method are presented for dynamically generated reports. In an embodiment, a first device is associated with events, such that when the events occur, they trigger the sending of information to a second device. The second device accesses information relating to the first device and uses this information to generate data and/or alerts related to the first device. In an embodiment, the events associated with the first device comprise crossing a pre-determined geo-fence, specific GPS coordinates, networks, etc. Events may also originate from user actions in an application and external sources.

Abstract: A system and method are presented for dynamically generated reports. In an embodiment, a first device is associated with events, such that when the events occur, they trigger the sending of information to a second device. The second device accesses information relating to the first device and uses this information to generate data and/or alerts related to the first device. In an embodiment, the events associated with the first device comprise crossing a pre-determined geo-fence, specific GPS coordinates, networks, etc. Events may also originate from user actions in an application and external sources.

Abstract: A method of automatically labeling of unlabeled text data can be practiced independent of human intervention, but that does not preclude manual intervention. The method can be used to extract relevant features of unlabeled text data for a keyword search. The method of automated labeling of unlabeled text data uses a document collection as a reference answer set. Members of the answer set are converted to vectors representing centroids of unknown groups of unlabeled text data. Unlabeled text data are clustered relative to the centroids by a nearest neighbor algorithm and the ID of the relevant answer is assigned to all documents in the cluster. At this point in the process, a supervised machine learning algorithm is trained on labeled data, and a classifier for assigning labels to new text data is output. Alternatively, a feature extraction algorithm may be run on classes generated by the step of clustering, and search features output which index the unlabeled text data.

Abstract: Methods, systems and computer program products are provided which automatically distribute tasks associated with a telephone system and tasks associated with a computer system between a plurality of agents tracking ACD telephone status of the plurality of agents and tracking computer status of the plurality of agents. When a request for a computer task is received, an agent of the plurality of agents is assigned to the computer task corresponding to the received request based on the ACD telephone status and the computer status of the agent of the plurality of agents.

Abstract: A machine learning based electronic mail system. A classifier and action selection module analyzes the incoming message and classifies the messages with associated confidence levels, which may include analyzing the electronic message by tokenization of the text, morphological analysis of the text, and other well known processes. The classifier and action selection module then determines the appropriate action or actions to effect on the message.