Abstract: Text is intelligently annotated by first creating a topic map summarizing topics of interest of the user. A data structure is created. The topic map is used to create two linked user dictionaries, a topic dictionary reflecting topic names and a traversal dictionary reflecting the knowledge structure of a topic. Actions may be linked with topic types. When the text to be annotated is being read, the topic data structure of the topics found in the text are automatically instantiated using the dictionaries and any actions previously linked to topic types. Instantiated topic data structures are automatically attached to the text being annotated. A user GUI may be created to allow the user to access and interact with the text annotations.

Abstract: For confidence weighting relationships between complex entities in unstructured data an expressed relationship between a subset of a set of tokens is extracted from a knowledge graph corresponding to the unstructured data. The knowledge graph includes the set of tokens. The tokens in the subset of tokens are related in the expressed relationship by a set of predicates. A number of occurrences of the set of predicates in the unstructured data is determined. A number of occurrences of the expressed relationship in the unstructured data is determined. Using the number of occurrences of the set of predicates and the number of occurrences of the expressed relationship, a confidence value is computed and assigned to the expressed relationship.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: During a live stream of a main content to a user, a biometric response of the user is measured during a first streamed portion of the main content. The biometric response is analyzed to detect an event in the first streamed portion of the main content. The biometric response of the user during the event indicates that the event is a user-specific climactic event. Based on the analysis, a user-specific set of feature values is computed that are representative of the user-specific climactic event in the first streamed portion of the main content. A user-specific non-climactic period is forecasted in a future portion of the live stream during which a likelihood of an occurrence of any user-specific climactic event is below a threshold likelihood. A secondary content is inserted during the user-specific non-climactic period.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: From a directional acyclic graph (DAG) corresponding to a data volume, a matrix of relationships of a first node and a second node is computed. The DAG includes a set of nodes and a set of directional edges, the set of nodes including the first node and the second node. An inverted matrix is computed from the matrix, which retains values in only those column positions where a value in a first row corresponding to the first node is opposite of a value in a second row corresponding to the second node. From the first row, a first cluster of nodes related to the first node is constructed by selecting nodes corresponding to those columns where the first row has a value indicating an affirmative relationship. Information representing the first cluster of nodes a second cluster of nodes are output.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: A method, system, and computer program product for identifying related information in dissimilar data are provided in the illustrative embodiments. Using a first part of a first entry in a dictionary, a first portion is identified in a first data, the first part matching the first portion within a tolerance. A second part of the first entry referencing a section of a second data is determined, the second data being organized in a repository according to a schema. A third part of the first entry sufficient to locate a record in the section of the second data is determined. A query is constructed using the second part and the third part, and performed on the second data. A result set is obtained, wherein a record in the result set is related to the first portion in the first data and the record does not include the first portion.

Abstract: Systems and methods for autonomic positioning of overlays within streaming data are disclosed. In embodiments, a computer-implemented method comprises: providing a hosted data stream containing a first display object to a plurality of participants through respective participant devices; providing a hosted second display object to the plurality of participants through the respective participant devices, wherein the second display object is contained within an overlay that is positioned atop the first display object at a first position; calculating consensus coordinates for the second display object based on suggested position data received from the respective participant devices; calculating customized coordinates for the second display object for each of the respective participant devices based on the consensus coordinates and participant data; and sending the customized coordinates to each of the respective participant devices.

Abstract: From a live streaming of a main content, an already streamed portion of the main content is analyzed to identify an occurrence of a climactic event in the main content. Based on the analysis, a set is constructed of feature values that are representative of the climactic event in the already streamed portion of the main content. A non-climactic period is forecasted during which a likelihood of an occurrence of any climactic event is below a threshold likelihood. A secondary content is inserted in the live streaming of the main content during the non-climactic period, such that a likelihood of the secondary content insertion interrupting the live streaming during a second climactic event is less than a second threshold of likelihood. The live streaming of the main content is continued after the secondary content is completely transmitted in the live streaming.

Abstract: A non-climactic period is forecasted during a live streaming of a main content, where a likelihood of an occurrence of any climactic event in the non-climactic period is below a threshold likelihood, and where a second content is inserted during the non-climactic period. A validation is requested from a first user of the live streaming, of the forecasted non-climactic period and a first response to the request is received from the first user. Based on the first response, a first rank of the first user is computed relative to another user in a group of responding users. A first dynamic delay period that has an inverse relationship with the first rank is computed for the first user. A first transmission of a future portion of the live streaming to the first user is delayed by at least the first dynamic delay period.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: Embodiments described herein provide approaches for validating synonyms in ontology driven natural language processing. Specifically, an approach is provided for receiving a user input containing a token, structuring the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token, designating the token as a synonym of one of the set of related permutations, annotating the token with a class from the set of classes corresponding to the one of the set of related permutations, and validating the annotation of the token by determining an accuracy of the designation of the token as a synonym of the one of the set of related permutations. In one embodiment, the accuracy is determined by quantifying a linear distance between the token and a contextual token also within the user input, and comparing the linear distance to a pre-specified linear distance limit.

Abstract: During a live stream of a main content to a user, a biometric response of the user is measured during a first streamed portion of the main content. The biometric response is analyzed to detect an event in the first streamed portion of the main content. The biometric response of the user during the event indicates that the event is a user-specific climactic event. Based on the analysis, a user-specific set of feature values is computed that are representative of the user-specific climactic event in the first streamed portion of the main content. A user-specific non-climactic period is forecasted in a future portion of the live stream during which a likelihood of an occurrence of any user-specific climactic event is below a threshold likelihood. A secondary content is inserted during the user-specific non-climactic period.

Abstract: A non-climactic period is forecasted during a live streaming of a main content, where a likelihood of an occurrence of any climactic event in the non-climactic period is below a threshold likelihood, and where a second content is inserted during the non-climactic period. A validation is requested from a first user of the live streaming, of the forecasted non-climactic period and a first response to the request is received from the first user. Based on the first response, a first rank of the first user is computed relative to another user in a group of responding users. A first dynamic delay period that has an inverse relationship with the first rank is computed for the first user. A first transmission of a future portion of the live streaming to the first user is delayed by at least the first dynamic delay period.

Abstract: During a live stream of a main content to a user, a biometric response of the user is measured during a first streamed portion of the main content. The biometric response is analyzed to detect an event in the first streamed portion of the main content. The biometric response of the user during the event indicates that the event is a user-specific climactic event. Based on the analysis, a user-specific set of feature values is computed that are representative of the user-specific climactic event in the first streamed portion of the main content. A user-specific non-climactic period is forecasted in a future portion of the live stream during which a likelihood of an occurrence of any user-specific climactic event is below a threshold likelihood. A secondary content is inserted during the user-specific non-climactic period.

Abstract: Systems and methods for autonomic positioning of overlays within streaming data are disclosed. In embodiments, a computer-implemented method comprises: providing a hosted data stream containing a first display object to a plurality of participants through respective participant devices; providing a hosted second display object to the plurality of participants through the respective participant devices, wherein the second display object is contained within an overlay that is positioned atop the first display object at a first position; calculating consensus coordinates for the second display object based on suggested position data received from the respective participant devices; calculating customized coordinates for the second display object for each of the respective participant devices based on the consensus coordinates and participant data; and sending the customized coordinates to each of the respective participant devices.

Abstract: During a live stream of a main content to a user, a biometric response of the user is measured during a first streamed portion of the main content. The biometric response is analyzed to detect an event in the first streamed portion of the main content. The biometric response of the user during the event indicates that the event is a user-specific climactic event. Based on the analysis, a user-specific set of feature values is computed that are representative of the user-specific climactic event in the first streamed portion of the main content. A user-specific non-climactic period is forecasted in a future portion of the live stream during which a likelihood of an occurrence of any user-specific climactic event is below a threshold likelihood. A secondary content is inserted during the user-specific non-climactic period.

Abstract: From a live streaming of a main content, an already streamed portion of the main content is analyzed to identify an occurrence of a climactic event in the main content. Based on the analysis, a set is constructed of feature values that are representative of the climactic event in the already streamed portion of the main content. A non-climactic period is forecasted during which a likelihood of an occurrence of any climactic event is below a threshold likelihood. A secondary content is inserted in the live streaming of the main content during the non-climactic period, such that a likelihood of the secondary content insertion interrupting the live streaming during a second climactic event is less than a second threshold of likelihood. The live streaming of the main content is continued after the secondary content is completely transmitted in the live streaming.

Abstract: A non-climactic period is forecasted during a live streaming of a main content, where a likelihood of an occurrence of any climactic event in the non-climactic period is below a threshold likelihood, and where a second content is inserted during the non-climactic period. A validation is requested from a first user of the live streaming, of the forecasted non-climactic period and a first response to the request is received from the first user. Based on the first response, a first rank of the first user is computed relative to another user in a group of responding users. A first dynamic delay period that has an inverse relationship with the first rank is computed for the first user. A first transmission of a future portion of the live streaming to the first user is delayed by at least the first dynamic delay period.