Abstract: Apparatuses and methods concerning providing a data-communications virtual assistant are disclosed. As an example, one apparatus includes a data-communications server. The data-communications server is configured to process user-data-communications between a client station and another station participating in data-communications via the data-communications services where the client station is associated with one client entity. The server is also configured to identify a context for each respective user-data-communication between the client station and the participating station, where the context data corresponds to at least one communications-specific characteristic associated with the user-data-communications, and to retrieve structured and unstructured data relating to previous data-communications provided by the data-communications server.

Abstract: Apparatuses and methods concerning providing a data-communications contact center virtual agent are disclosed. As an example, user-data-communications between client and participant stations are facilitated as follows, which may be implemented using a data communications server and associated communications circuitry. Service request data is received from users at a participant stations, and context information is identified for user-data-communications between a client station and the participant stations based on the service request data at least one communications-specific characteristic associated with the user-data-communications. The identified context information is aggregated for the client station and used for choosing a data routing option routing data with each user at the participant stations, based on the service request data and the aggregated context information.

Abstract: Apparatuses and methods concerning providing a data-communications virtual assistant are disclosed. As an example, one apparatus includes a data-communications server. The data communications server is configured to process user-data-communication between a client station and another client station participating in data-communications via the data-communications server, where each client station is associated with one client entity. The server is also configured to identify a context for each user-data-communication between the client station and the other client station, where the context corresponds to at least one communications-specific characteristic associated with the user-data-communication. The server is further configured to apply call routing based on the identified context.

Abstract: Apparatuses and methods concerning providing data-communications room recommendations are disclosed. As an example, one apparatus includes a data-communications server. The data-communications server is configured to provide user-data-communications sessions. The server is also configured to retrieve data-communications messages, which may arise from a plurality of disparate interconnected data-communications systems, and batch the data communications messages for a particular data-communications room together to create a room document. Responding to receipt of a request from a particular user, the server identifies a particular data-communications room for a particular inquiry.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

Abstract: Apparatuses and methods concerning providing a data-communications virtual assistant are disclosed. As an example, one apparatus includes a data-communications server. The data-communications server is configured to process user-data-communications between a client station and another station participating in data-communications via the data-communications services where the client station is associated with one client entity. The server is also configured to identify a context for each respective user-data-communication between the client station and the participating station, where the context data corresponds to at least one communications-specific characteristic associated with the user-data-communications, and to retrieve structured and unstructured data relating to previous data-communications provided by the data-communications server.

Abstract: Apparatuses and methods concerning providing a data-communications contact center virtual agent are disclosed. As an example, user-data-communications between client and participant stations are facilitated as follows, which may be implemented using a data communications server and associated communications circuitry. Service request data is received from users at a participant stations, and context information is identified for user-data-communications between a client station and the participant stations based on the service request data at least one communications-specific characteristic associated with the user-data-communications. The identified context information is aggregated for the client station and used for choosing a data routing option routing data with each user at the participant stations, based on the service request data and the aggregated context information.

Abstract: Embodiments provide a computer implemented method in a data processing system including a processor and a memory, the memory including instructions that are executed by the processor to cause the processor to implement a system for generating a type system. The method includes: receiving a document corpus; identifying frequently occurring words from the document corpus, disregarding stop words; extracting a conceptual text for each frequently occurring word from a structured information database; performing a cluster analysis on each conceptual text to identify possible entity types; performing a frequency analysis on possible entity types to select at least one entity type; identifying a relation type between entities in the document corpus; and generating the type system including entity types and relation types.

Abstract: A mechanism is provided in a data processing system for solving a textual logic problem. A logic problem solution engine in the data processing system receives an input text containing a logic problem. A parser executing in the data processing system parses the input text to identify entities in the input text. The logic problem solution engine performs cognitive processing on the input text to discover relationships between the entities. A statistical analysis component executing in the data processing system determines statistical relationships between pairs of entities in the input text to form a set of statistical relationships. The logic problem solution engine determines whether a given statistical relationship within the set of statistical relationships fits as a solution to the logic problem.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

Abstract: A mechanism is provided in a data processing system for identifying a logic problem to be solved in an input text. A parser executing in the data processing system parses the input text to identify entities in the input text. A statistical analysis component executing in the data processing system determines statistical relationships between pairs of entities in the input text to form a set of statistical relationships. A logic problem detection engine executing in the data processing system determines whether the set of statistical relationships includes a high density of standard relationships and one or more outlier relationships. Responsive to determining that the set of statistical relationships includes a high density of standard relationships and one or more outlier relationships, the mechanism presents an indication that the input text includes a logic problem to a user.

Abstract: Embodiments provide a computer implemented method in a data processing system including a processor and a memory, the memory including instructions that are executed by the processor to cause the processor to implement a system for generating a type system. The method includes: receiving a document corpus; identifying frequently occurring words from the document corpus, disregarding stop words; extracting a conceptual text for each frequently occurring word from a structured information database; performing a cluster analysis on each conceptual text to identify possible entity types; performing a frequency analysis on possible entity types to select at least one entity type; identifying a relation type between entities in the document corpus; and generating the type system including entity types and relation types.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

Abstract: Natural language processing is enhanced by linguistically extracting intelligence about a user. A history of user queries is analyzed by a natural language classifier to determine various user intents, and these intents are combined to form a user intent profile. The profile includes elements of sentiment, emotion and tone. The profile can be used in various ways including restricting access to documents in a collection, or refining a cognitive analysis of a query. For access restriction, a determination is made that the user intent is inconsistent with a document, and the user is denied access to the document. This determination involves a user intent score which is compared to a score of the document. For cognitive analysis, searching of reference documents is filtered by excluding documents based on the user intent. The searching includes a comparison of meta-data tags of the documents to the user intent.

Abstract: A mechanism is provided in a data processing system for solving a textual logic problem. A logic problem solution engine in the data processing system receives an input text containing a logic problem. A parser executing in the data processing system parses the input text to identify entities in the input text. The logic problem solution engine performs cognitive processing on the input text to discover relationships between the entities. A statistical analysis component executing in the data processing system determines statistical relationships between pairs of entities in the input text to form a set of statistical relationships. The logic problem solution engine determines whether a given statistical relationship within the set of statistical relationships fits as a solution to the logic problem.

Abstract: A mechanism is provided in a data processing system for identifying a logic problem to be solved in an input text. A parser executing in the data processing system parses the input text to identify entities in the input text. A statistical analysis component executing in the data processing system determines statistical relationships between pairs of entities in the input text to form a set of statistical relationships. A logic problem detection engine executing in the data processing system determines whether the set of statistical relationships includes a high density of standard relationships and one or more outlier relationships. Responsive to determining that the set of statistical relationships includes a high density of standard relationships and one or more outlier relationships, the mechanism presents an indication that the input text includes a logic problem to a user.