Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria within a form. Natural Language Processing (NLP) is applied to unstructured data within a target form to identify elements of a form structure. Analytic analysis is then applied to the resulting form structure elements to identify a hierarchical structure and associated element placement. Implicit selections within the form are then identified by applying rules based upon other selections and their orientation to anchor terms to determine the completeness of the form, based upon aggregation of form elements. The form structure elements and the hierarchy metadata are then processed logically reassemble the form's hierarchy in flattened forms for multi-layer, sub-element anaphora resolution.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria within a form. Natural Language Processing (NLP) is applied to unstructured data within a target form to identify elements of a form structure. Analytic analysis is then applied to the resulting form structure elements to identify a hierarchical structure and associated element placement. Implicit selections within the form are then identified by applying rules based upon other selections and their orientation to anchor terms to determine the completeness of the form, based upon aggregation of form elements. The form structure elements and the hierarchy metadata are then processed logically reassemble the form's hierarchy in flattened forms for multi-layer, sub-element anaphora resolution.

Abstract: Information including a data set indicative of a problem concern is determined by changing an active/past state of the data from an active state to a past state based on a time of an update (e.g., time of an update of a diagnosis, when a file may be updated) indicative of a resolution of the problem concern. When a most recent entry in the data set exceeds a duration range for the problem concern as determined by a knowledge base, the active/past state of the data is changed from the active state to the past state. Further, it determines whether the problem concern is correlated with a treatment. When the correlated treatment is being taken by a subject, changing the active/past state of the data from the active state to the past state so as to provide diagnostic assistant tool.

Abstract: Information including data indicative of a problem concern is determined by changing an active/past state of the data from an active state to a past state based on a time of an update (e.g., time of an update of a diagnosis, when a file may be updated) indicative of a resolution of the problem concern. When a most recent entry in the data exceeds a duration range for the problem concern as determined by a knowledge base, the active/past state of the data is changed from the active state to the past state. Further, it determines whether the problem concern is correlated with a treatment. When the correlated treatment is being taken by a subject, changing the active/past state of the data from the active state to the past state so as to provide diagnostic assistant tool to a clinician for a meeting with the subject.

Abstract: A processor-implemented method constructs and utilizes an ontological graph. One or more processor(s) receive a seed term from a user, and then receive a first expansion signal from the user. In response to receiving the first expansion signal, the processor(s) automatically generate an ontological graph. The processor(s) display terms from the ontological graph as string literals in a dictionary, which contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term. The processor(s) then receive a second expansion signal from the user. In response to receiving the second expansion signal, the processor(s) expand the ontological graph to display additional terms that are related to the nodes represented in the ontological graph that was generated by the first expansion signal.

Abstract: A processor-implemented method constructs and utilizes an ontological graph. One or more processor(s) receive a seed term from a user, and then receive a first expansion signal from the user. In response to receiving the first expansion signal, the processor(s) automatically generate an ontological graph. The processor(s) display terms from the ontological graph as string literals in a dictionary, which contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term. The processor(s) then receive a second expansion signal from the user. In response to receiving the second expansion signal, the processor(s) expand the ontological graph to display additional terms that are related to the nodes represented in the ontological graph that was generated by the first expansion signal.

Abstract: A method, system, and/or computer program product constructs and utilizes an ontological graph. A seed term and an expansion signal are received from a user. An ontological graph is constructed based on the expansion signal as applied to the seed term. The ontological graph includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, such that the seed term and the other terms share a common trait. Terms from the ontological graph are displayed as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term.

Abstract: A method, system, and/or computer program product constructs and utilizes an ontological graph. A seed term and an expansion signal are received from a user. An ontological graph is constructed based on the expansion signal as applied to the seed term. The ontological graph includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, such that the seed term and the other terms share a common trait. Terms from the ontological graph are displayed as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria within a form. Natural Language Processing (NLP) is applied to unstructured data within a target form to identify elements of a form structure. Analytic analysis is then applied to the resulting form structure elements to identify a hierarchical structure and associated element placement. Implicit selections within the form are then identified by applying rules based upon other selections and their orientation to anchor terms to determine the completeness of the form, based upon aggregation of form elements. The form structure elements and the hierarchy metadata are then processed logically reassemble the form's hierarchy in flattened forms for multi-layer, sub-element anaphora resolution.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria within a form. Natural Language Processing (NLP) is applied to unstructured data within a target form to identify elements of a form structure. Analytic analysis is then applied to the resulting form structure elements to identify a hierarchical structure and associated element placement. Implicit selections within the form are then identified by applying rules based upon other selections and their orientation to anchor terms to determine the completeness of the form, based upon aggregation of form elements. The form structure elements and the hierarchy metadata are then processed logically reassemble the form's hierarchy in flattened forms for multi-layer, sub-element anaphora resolution.

Abstract: A method, a system and a computer program product for selecting a further inquiry for a user to clarify a request for information from the user. One or more candidate answers to the request for information from the user are determined, and a score value is generated for each of one or more characteristics of each candidate answer, where at least one characteristic is associated with an inquiry for the user to clarify the request for information. A characteristic associated with an inquiry is determined that includes score values providing the greatest potential adjustment for the candidate answers in response to a clarification of the request for information, and the inquiry is selected that is associated with the determined characteristic for presentation to the user.

Abstract: A method, system, and/or computer program product constructs and utilizes an ontological graph. A seed term and an expansion signal are received from a user. An ontological graph is constructed based on the expansion signal as applied to the seed term. The ontological graph includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, such that the seed term and the other terms share a common trait. Terms from the ontological graph are displayed as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term.

Abstract: A method, system, and/or computer program product constructs and utilizes an ontological graph. A seed term and an expansion signal are received from a user. An ontological graph is constructed based on the expansion signal as applied to the seed term. The ontological graph includes nodes representing the seed term plus other terms that are located in accordance with instructions derived from the first expansion signal, such that the seed term and the other terms share a common trait. Terms from the ontological graph are displayed as string literals in a dictionary, wherein the dictionary contains related other terms at a resolution level that is controlled by the first expansion signal from the user and the seed term.

Abstract: A memory management system is implemented at an application server. The management system includes a configuration file including configuration settings for the application server and applications. The configuration settings include multiple memory management rules. The management system also includes a memory management framework configured to manage settings of resources allocated to the applications based on the memory management rules. The applications requests for the resources through one or more independently operable request threads. The management system also includes multiple application programming interfaces (APIs) configured to facilitate communication between the applications and the memory management framework. The management system further includes a monitoring engine configured to monitor an execution of the request threads and perform actions based upon the configuration settings.

Abstract: A peer group can be established for sharing Web cache data among a set of computing devices through a peer-to-peer network. The Web cache data can be used by each of the computing devices to respond to requests issued over a client-server network from a Web browser running on that computing device. Web cache data can be exchanged among the peers of the peer group via the peer-to-peer network. A client request issued from a Web browser of one of the computing devices can be satisfied using Web cache data obtained from a different one of the computing devices in the peer group. The client request can be a request to one of the Web servers for Web content. The server associated with the request may never provide the Web content responsive to the client request, which is obtained instead from the different one of the computing devices.

Abstract: A method and system for enhancing problem resolution at a call center based on speech recognition of a caller includes, receiving an incoming call and generating call data based on speech recognition of the incoming call using a computer. The method generates and associates annotated metadata about the call data. A historical record is created which includes the call data and the annotated metadata. The historical record may be stored in a storage medium communicating with the computer. Context data is generated for the incoming call by analyzing the historical record to identify: a caller, a topic, a date and a stress level of the caller. The method compares the context data to historical records of previous calls. A topic probabilities analysis is conducted by comparing the context data to the historical records of previous calls, and a solution is determined for the topic based on the probabilities analysis.

Abstract: Provided is a Captcha Access Control System (CACS) for generating an improved captcha that are based, in one described embodiment, upon a command in one format and a response in a different format, one or both of which are rendered in a format that is difficult for an automated system to interpret. A computer system or program to which a user is requesting access generates a textual or audible command. A video device captures the user's response and transmits the response to a response evaluation device. Based upon an analysis of the transmitted video and a comparison between the analyzed video and the command, the computer or program either enables access or denies access.

Abstract: A memory management system is implemented at an application server. The management system includes a configuration file including configuration settings for the application server and applications. The configuration settings include multiple memory management rules. The management system also includes a memory management framework configured to manage settings of resources allocated to the applications based on the memory management rules. The applications requests for the resources through one or more independently operable request threads. The management system also includes multiple application programming interfaces (APIs) configured to facilitate communication between the applications and the memory management framework. The management system further includes a monitoring engine configured to monitor an execution of the request threads and perform actions based upon the configuration settings.

Abstract: A method and system for enhancing problem resolution at a call center based on speech recognition of a caller includes, receiving an incoming call and generating call data based on speech recognition of the incoming call using a computer. The method generates and associates annotated metadata about the call data. A historical record is created which includes the call data and the annotated metadata. The historical record may be stored in a storage medium communicating with the computer. Context data is generated for the incoming call by analyzing the historical record to identify: a caller, a topic, a date and a stress level of the caller. The method compares the context data to historical records of previous calls. A topic probabilities analysis is conducted by comparing the context data to the historical records of previous calls, and a solution is determined for the topic based on the probabilities analysis.

Abstract: A method, a system and a computer program product for selecting a further inquiry for a user to clarify a request for information from the user. One or more candidate answers to the request for information from the user are determined, and a score value is generated for each of one or more characteristics of each candidate answer, where at least one characteristic is associated with an inquiry for the user to clarify the request for information. A characteristic associated with an inquiry is determined that includes score values providing the greatest potential adjustment for the candidate answers in response to a clarification of the request for information, and the inquiry is selected that is associated with the determined characteristic for presentation to the user.