Abstract:
A method for deploying an additional document classifier engine into an existing document processing system that includes the steps of adding a new document classifier engine to an existing single or pool of document classifier engines and training the new document classifier engine on previously misclassified documents.
Abstract:
Systems, methods, and programs embodied in a computer readable medium are provided for index extraction. A plurality of ground truth documents are stored in a database, the ground truth documents being organized in a plurality of classifications. Attempts are made to automatically extract indices from a document based upon a classification associated with the document. The document is reclassified from a first one of the classifications to a second one of the classifications during the course of the automated extraction of the indices by drawing an association between the document and at least one of the ground truth documents. The indices are manually extracted from the document upon a failure to automatically extract the indices. The document is stored in the database as one of the ground truth documents if the indices are manually extracted.
Abstract:
Systems, methods, and programs embodied in a computer readable medium are provided for index extraction. An extraction of a plurality of sets of indices from a document in a server is implemented using a plurality of indexing entities. Each set of indices is extracted using a corresponding one of the indexing entities. Attempts are made to obtain a composite set of indices from the sets of indices extracted. The composite set of indices is associated with the document if the composite set of indices is successfully obtained from the sets of indices.
Abstract:
A method of classifying a document includes providing a plurality of classifier engines and classifying the document using output from one or more of the classifier engines based on a comparison of one or more metrics for each classifier engine. In another embodiment, a method of classifying a document comprises providing a plurality of classifier engines and determining one or more metrics for each classifier engine. These metrics are used to determine how to use the classifier engines to classify the document, and the document is classified accordingly. A further embodiment includes a document classifier utilizing a plurality of classifier engines. In yet another embodiment, a computer-readable medium contains instructions for controlling a computer system to perform a method of using a plurality of classifier engines to classify a document.
Abstract:
Systems, methods, and programs embodied in a computer readable medium are provided for index extraction. Stored in a database are ground truth documents that are organized according to a plurality of classifications, each classification having a group of predefined indices. A document to be indexed is classified by drawing an association between the document and one of the classifications. An attempt is made to extract from the document at least a subset of the group of predefined indices associated with the one of the classifications. Upon a failure to extract the subset of the group of predefined indices, attempts are made to find and correct at least one text recognition error in the document based upon a salient dictionary associated with the one of the classifications.
Abstract:
A method for generating a modifiable summary of medical data derived from a patient can comprise steps of selecting a subset of medical data from a medical database, wherein the subset at least partially is uniquely associated with an individual patient, and generating a living graphical representation from at least a portion of the subset. The living graphical representation can be dynamically reconfigurable upon modification of the portion. In another embodiment, a method for customizing patient medical information for presentation to a patient as a customized file can comprise steps of determining a medical condition of a patient, identifying static data related to the medical condition, and identifying dynamic data uniquely related to the patient. Additional steps can include forming a customized file of the patient from the static and dynamic data, wherein the customized file summarizes at least an episode of medical care.
Abstract:
A method for presenting content to an audience includes the steps of receiving a voice input from an audience member, determining the identity of the audience member, converting the voice input from the identified audience member to text, and presenting the text to the audience. A system that brings about the method is also described.
Abstract:
A system comprises a first speech recognition engine, a second speech recognition engine, and evaluation logic coupled to the first and second speech recognition engines. The evaluation logic evaluates the first and second speech recognition engines based on evaluation voice signals from a user and, based on the evaluation, selects one of said speech recognition engines to process additional speech signals from the user.
Abstract:
In at least some embodiments, a system may comprise a user voice interface, a processor coupled to the user voice interface, wherein the processor interprets words spoken by a user, and a memory coupled to the processor, wherein the memory stores an email application, wherein the email application summarizes email messages and navigates a plurality of email messages according to the words spoken by the user.
Abstract:
A system for distinguishing a package includes a plurality of identifiers, where at least one of the identifiers is intentionally non-functional. The system also includes an identifier indicator that indicates the identity of the at least one of the identifiers that is intentionally non-functional. In addition, the identifier indicator is stored on at least one of the package and a database and is accessible by a user to authenticate the package.