Abstract: Presenting unique search result contexts, including: receiving, by a search result presentation module, a plurality of search results generated in response to a search query, wherein each search result includes context information associated with the search result; identifying, by the search result presentation module for each search result, a displayable portion of the context information associated with the search result; determining, by the search result presentation module for each search result, whether the displayable portion of the context information is a duplicate of the displayable portion of the context information for another search result; and responsive to determining that the displayable portion of the context information is a duplicate of the displayable portion of the context information for another search result, updating, by the search result presentation module, the displayable portion of the context information for the search result.

Abstract: A digital work of literature is vocalized using enhanced text-to-speech (TTS) controls by analyzing a digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, each quote being associated with audio synthesis control parameters for the TTS in the context of each the quotes in the work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the work of literature according to the words of each quote, character voice characteristics of corresponding to each quote, and context corresponding to each quote.

Abstract: A digital work of literature is vocalized using enhanced text-to-speech (TTS) controls by analyzing a digital work of literature using natural language processing to identify speaking character voice characteristics associated with context of each quote as extracted from the first work of literature; converting the character voice characteristics to audio metadata to control text-to-speech audio synthesis for each quote; transforming the audio metadata into text-to-speech engine commands, each quote being associated with audio synthesis control parameters for the TTS in the context of each the quotes in the work of literature; and inputting the commands to a text-to-speech engine to cause vocalization of the work of literature according to the words of each quote, character voice characteristics of corresponding to each quote, and context corresponding to each quote.

Abstract: A computer-implemented method detects a stability change in a first computer system, and compares a first set of software applications installed on the first computer system to each set of software applications installed on a plurality of other computer systems. The method then identifies a second computer system from among the plurality of other computer systems, wherein the set of software applications installed on the second computer system includes all of the first set of software applications except for a given software application. The given software application is then identified as the cause of the stability change in the first computer system. The computer systems are preferably virtual machines being managed by a management module, such as a provisioning manager. The method may be used to detect both increases in stability and instability.

Abstract: A computer program product including computer usable program code embodied on a tangible computer usable storage medium, includes: computer usable program code for detecting a stability change in a first computer system; computer usable program code for comparing a first set of software applications installed on the first computer system to each set of software applications installed on a plurality of other computer systems in communication with a management module; computer usable program code for identifying a second computer system from among the plurality of other computer systems, wherein the set of software applications installed on the second computer system includes all of the first set of software applications except for a given software application; and computer usable program code for identifying the given software application as the cause of the stability change in the first computer system.

Abstract: Embodiments of the present invention provide methods and apparatuses enabling groupware to track time associated with a workflow task. A workflow object representing a workflow task is provided. The workflow object is associating with a time period, a project code, and an identifier of a groupware client user participating in the workflow task. In response to an event indicating completion of the workflow task, the time period, the project code, and the identifier is automatically transmitted to a backend application.

Abstract: Automatic distribution of image data, such as a digital photographs, is prevented or delayed if the photograph is determined to likely contain confidential data. Online photo streaming services, albums, social media accounts, and backup services can be a source of inadvertent disclosure of confidential information due to these automatic dissemination functions of modern photo capturing devices. Detection criteria to trigger the blocking of dissemination may include recognition of faces of co-workers and clients, recognition of business furnishings such as whiteboards and conference room equipment, as well as geotags where the image was captured, the time, day of week, and date at which it was captured, and network identifiers associated with the network on which the capturing device is connected.

Abstract: Dynamically recommending changes to an association between an operating system image and an update group includes monitoring a configuration of a deployed copy of a first master operating system (OS) image; detecting a modification in the configuration of the deployed copy; determining that the configuration of the deployed copy with the modification more closely matches a configuration of a second master OS image than a configuration of the first master OS image; in response to determining that the configuration of the deployed copy with the modification more closely matches the configuration of the second master OS image, generating an association recommendation that recommends associating the deployed copy with a second update group of the second master OS image; and associating the deployed copy with the second update group of the second master OS image instead of the first update group of the first master OS image.

Abstract: Presenting unique search result contexts, including: receiving, by a search result presentation module, a plurality of search results generated in response to a search query, wherein each search result includes context information associated with the search result; identifying, by the search result presentation module for each search result, a displayable portion of the context information associated with the search result; determining, by the search result presentation module for each search result, whether the displayable portion of the context information is a duplicate of the displayable portion of the context information for another search result; and responsive to determining that the displayable portion of the context information is a duplicate of the displayable portion of the context information for another search result, updating, by the search result presentation module, the displayable portion of the context information for the search result.

Abstract: Users of online services may avoid having to gain knowledge of the intricacies of specific Application Programming Interface (API) syntaxes and elements by using natural language requests which are processed to extract components of the request. The components are then used to find one or more matches of known APIs, and then at least one structured API call is constructed by mapping the request's components to the structured API call's elements. The system can then invoke the online service on behalf of the client, and return the results to the client, or it can return the constructed structured API call to the client. The known API details can be initialized and updated by ingesting the description documents for the structured APIs, and then using natural language processing to extract components from the descriptions, which can then be utilized in the matching process to further enhance the results of the tool.

Abstract: Users of online services may avoid having to gain knowledge of the intricacies of specific Application Programming Interface (API) syntaxes and elements by using natural language requests which are processed to extract components of the request. The components are then used to find one or more matches of known APIs, and then at least one structured API call is constructed by mapping the request's components to the structured API call's elements. The system can then invoke the online service on behalf of the client, and return the results to the client, or it can return the constructed structured API call to the client. The known API details can be initialized and updated by ingesting the description documents for the structured APIs, and then using natural language processing to extract components from the descriptions, which can then be utilized in the matching process to further enhance the results of the tool.

Abstract: An approach is provided for detecting and monitoring end user license agreement (EULA) compliance is provided. A request to access a executable software code is received from an end user. A EULA version corresponding to the requested executable software code is identified. A determination is made as to whether the end user has accepted the identified EULA. If the end user has not accepted the identified EULA, then an out of date EULA notification is sent to the end user, the EULA is sent to the end user requesting an acceptance to the EULA. A EULA response is received from the end user. If the end user accepts the EULA, then the end user is allowed access to the executable software code.

Abstract: Administering text message communications, including: maintaining, by a service provider, an account age for a plurality of phone numbers; receiving, by the service provider from a mobile communications device, a text message intended to be delivered to a target device associated with a phone number, the text message including metadata describing an address book age of the phone number in an address book of the mobile communications device; determining, by the service provider, whether the address book age of the phone number is older than an account age of the phone number; and responsive to determining that the address book age information of the phone number is older than the account age of the phone number, performing, by the service provider, one or more message administration actions.

Abstract: Automatic distribution of image data, such as a digital photographs, is prevented or delayed if the photograph is determined to likely contain confidential data. Online photo streaming services, albums, social media accounts, and backup services can be a source of inadvertent disclosure of confidential information due to these automatic dissemination functions of modern photo capturing devices. Detection criteria to trigger the blocking of dissemination may include recognition of faces of co-workers and clients, recognition of business furnishings such as whiteboards and conference room equipment, as well as geotags where the image was captured, the time, day of week, and date at which it was captured, and network identifiers associated with the network on which the capturing device is connected.

Abstract: Automatic semantic analysis for characterizing and correlating literary elements within a digital work of literature is accomplished by employing natural language processing and deep semantic analysis of text to create annotations for the literary elements found in a segment or in the entirety of the literature, a weight to each literary element and its associated annotations, wherein the weight indicates an importance or relevance of a literary element to at least the segment of the work of literature; correlating and matching the literary elements to each other to establish one or more interrelationships; and producing an overall weight for the correlated matches.

Abstract: A visualization of literary elements of a work of literature, such as a novel or short story, is generated from meta-data records representing a digital work of literature including literary elements (humor, drama, adventure, etc.), characters, and plot devices related to a position within the work of literature where each appears. A significance level is determined for each of the elements, characters and plot devices at each position within the work of literature, and these are plotted into a sequential graph having position (e.g. timeline) axis and a significance level axis. The sequential graph is then output for printing or display. Human-generated and machine-generated meta-data may be ingested equally well by the method. Colors, line thickness, and a broken line patterns may be employed for greater visual meaning. And, the sequential graph may be annotated according to segments (e.g. chapters, sections) and dominant genre within each segment.

Abstract: Automatic semantic analysis for characterizing and correlating literary elements within a digital work of literature is accomplished by employing natural language processing and deep semantic analysis of text to create annotations for the literary elements found in a segment or in the entirety of the literature, a weight to each literary element and its associated annotations, wherein the weight indicates an importance or relevance of a literary element to at least the segment of the work of literature; correlating and matching the literary elements to each other to establish one or more interrelationships; and producing an overall weight for the correlated matches.

Abstract: A visualization of literary elements of a work of literature, such as a novel or short story, is generated from meta-data records representing a digital work of literature including literary elements (humor, drama, adventure, etc.), characters, and plot devices related to a position within the work of literature where each appears. A significance level is determined for each of the elements, characters and plot devices at each position within the work of literature, and these are plotted into a sequential graph having position (e.g. timeline) axis and a significance level axis. The sequential graph is then output for printing or display. Human-generated and machine-generated meta-data may be ingested equally well by the method. Colors, line thickness, and a broken line patterns may be employed for greater visual meaning. And, the sequential graph may be annotated according to segments (e.g. chapters, sections) and dominant genre within each segment.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.