Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria in unstructured and semi-structured data within a form. Text spans representing unchecked criteria within unstructured text in a form are detected and classified to facilitate accurate interpretation of the text. Section identification and annotation operations are then performed to identify and categorize sections within the form. Checklist sections within the form, along with associated checkmarks and boxes, are then identified, followed by the identification of checked item, criteria scope, and previously undetected checklist sections. Once all checklist sections and checked criteria have been identified, remaining text spans within a checklist section are annotated as unchecked criteria.

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 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 mechanism is provided for optimizing parsing of grammatical prose in a multi-prose electronic document. A received multi-prose electronic document is partitioned into a set of text segments of homogenous prose. A set of predefined Natural Language (NL) parsers is executed on each text segment in order to discern and measure a quality of parses by each NL parser throughout the multi-prose electronic document. A cross-parse analysis of the multi-prose electronic document and an aggregation of adjacent clauses or sentences of poor quality parses are performed. For each text segment, aggregation patterns yielding a best semantic role match are identified from one of the set of predefined NL parsers. Then, a parsed electronic document is generated using the set of predefined NL parsers such that each text segment is parsed by a NL parser that has the best semantic role match to that text segment.

Abstract: A method, system and computer-usable medium are disclosed for identifying unchecked criteria in unstructured and semi-structured data within a form. Text spans representing unchecked criteria within unstructured text in a form are detected and classified to facilitate accurate interpretation of the text. Section identification and annotation operations are then performed to identify and categorize sections within the form. Checklist sections within the form, along with associated checkmarks and boxes, are then identified, followed by the identification of checked item, criteria scope, and previously undetected checklist sections. Once all checklist sections and checked criteria have been identified, remaining text spans within a checklist section are annotated as unchecked criteria.

Abstract: A system and method for managing access rights to a project team area for a community development asset. The system includes an asset consumption dependency generator and a behavior pattern activity analyzer. The asset consumption dependency generator identifies a member of a project team area for a community development asset. The project team area defines access rights of individuals to the community development asset. The behavior pattern activity analyzer identifies a user within a collaborative development network associated with the identified member of the project team area. The behavior pattern activity analyzer also grants an access right to the identified user to access the community development asset based on a social map dependency between the identified user and the identified member.

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: A method, system and computer-usable medium are disclosed for identifying unchecked criteria in unstructured and semi-structured data within a form. Text spans representing unchecked criteria within unstructured text in a form are detected and classified to facilitate accurate interpretation of the text. Section identification and annotation operations are then performed to identify and categorize sections within the form. Checklist sections within the form, along with associated checkmarks and boxes, are then identified, followed by the identification of checked item, criteria scope, and previously undetected checklist sections. Once all checklist sections and checked criteria have been identified, remaining text spans within a checklist section are annotated as unchecked criteria.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.

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: 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.

Abstract: Mechanisms are provided for relational context sensitive anonymization of data. A request for data is received that specifies a relational context corresponding to a selected group of selected persons selected from a global group of persons based on the relational context. The relational context specifies one or more attributes of selected persons in the selected group that establishes a relationship between the selected persons and distinguishes the selected persons from non-selected persons in the global group that are not in the selected group. For the relational context, based on a corpus of personal information data corresponding to the selected persons, key attributes in the personal information data are determined and a rarity value for each key attribute is determined. Selected key attributes are then anonymized based on the determined rarity value for each of the key attributes within the relational context of the selected group.

Abstract: Mechanisms are provided for generating section metadata for an electronic document. These mechanisms receive a document and analyze the document to identify concepts present within textual content of the document. The mechanisms correlate concepts within the textual content with one another to identify concept groups based on the application of one or more rules defining related concepts or concept patterns. The mechanisms determine sections of text within the textual content based on the correlation of concepts within the textual content. Based on results of the determining, the mechanisms generate section metadata for the document and store the section metadata in association with the document for use by a document processing system.

Abstract: The Syndicated Web Services Client (SWSC) uses RSS/ATOM feeds, to facilitate asynchronous interactions between a computerized client and a web service, without requiring a duplicate copy of the web service application on the computerized client. The web service packages a form, such as an XForm containing interactive fields used by the web service, in a RSS/ATOM feed item. The web service sends the RSS/ATOM feed item to a computerized client, wherein the computerized client is a subscriber to the web service's RSS/ATOM feed and the computerized client is in network communication with a server hosting the web service. The computerized client displays the form for use by a user. Responsive to the user of the computerized client manipulating interactive fields in the form, the computerized client packages the manipulated form in a return. RSS/ATOM feed item.

Abstract: The Syndicated Web Services Client (SWSC) uses RSS/ATOM feeds, to facilitate asynchronous interactions between a computerized client and a web service, without requiring a duplicate copy of the web service application on the client. The web service packages an XForm containing interactive fields used by the web service in a RSS/ATOM feed item. The web service sends the RSS/ATOM feed item to the client, which is a subscriber to the web service's RSS/ATOM feed and is in network communication with a server hosting the web service. The client displays the form for use by a user. Responsive to the user of the client manipulating interactive fields in the form, the client packages the manipulated form in a return RSS/ATOM feed item. The client sends the return RSS/ATOM feed item to the server which is a subscriber to the client's return RSS/ATOM feed.

Abstract: Mechanisms are provided for resolving annotation conflicts in a portion of content. A portion of content is received and annotation operations are performed on it using a plurality of annotators. Each annotator in the plurality of annotators generates a set of annotations for the portion of content, thereby generating a plurality of sets of annotations for the portion of content. The plurality of sets of annotations are analyzed to identify a conflict between a first annotation and a second annotation in the plurality of sets of annotations. The conflict between the first annotation and the second annotation is resolved to generate a resultant set of annotations for the portion of content. The resultant set of annotations is stored in an annotations data structure associated with the portion of content.

Abstract: Mechanisms are provided for relational context sensitive anonymization of data. A request for data is received that specifies a relational context corresponding to a selected group of selected persons selected from a global group of persons based on the relational context. The relational context specifies one or more attributes of selected persons in the selected group that establishes a relationship between the selected persons and distinguishes the selected persons from non-selected persons in the global group that are not in the selected group. For the relational context, based on a corpus of personal information data corresponding to the selected persons, key attributes in the personal information data are determined and a rarity value for each key attribute is determined. Selected key attributes are then anonymized based on the determined rarity value for each of the key attributes within the relational context of the selected group.

Abstract: An apparatus includes memory, a processor and a visualization analysis unit coupled with the memory and the processor. The visualization analysis unit is configured to detect a visualizable subject matter contained within data. The visualization analysis unit is also configured to determine a context in which the visualizable subject matter appears. The visualization analysis unit is also configured to select a visualization engine from a plurality of visualization engines based, at least in part, on the context in which the visualizable subject matter appears. The visualization analysis unit is also configured to configure the visualization engine to generate a visualization of the visualizable subject matter.