Abstract: A mechanism is provided in a data processing system for tailoring question answering system output based on user expertise. The mechanism receives an input question from a questioning user and determines a set of features associated with text of the input question. The mechanism determines an expertise level of the questioning user based on the set of features associated with the text of the input question using a trained expertise model. The mechanism generates one or more candidate answers for the input question and tailors output of the one or more candidate answers based on the expertise level of the questioning user.

Abstract: A mechanism is provided in a data processing system for tailoring question answering system output based on user expertise. The mechanism receives an input question from a questioning user and determines a set of features associated with text of the input question. The mechanism determines an expertise level of the questioning user based on the set of features associated with the text of the input question using a trained expertise model. The mechanism generates one or more candidate answers for the input question and tailors output of the one or more candidate answers based on the expertise level of the questioning user.

Abstract: A mechanism is provided in a data processing system for tailoring question answering system output based on user expertise. The mechanism receives an input question from a questioning user and determines a set of features associated with text of the input question. The mechanism determines an expertise level of the questioning user based on the set of features associated with the text of the input question using a trained expertise model. The mechanism generates one or more candidate answers for the input question and tailors output of the one or more candidate answers based on the expertise level of the questioning user.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. Natural language content is received, upon which a reasoning operation is to be performed. A first parse representation of the natural language content is generated, by a parser, by performing natural language processing on the natural language content. A logical parse of the first parse is generated by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content. A reasoning operation on the logical parse is executed to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.

Abstract: An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.

Abstract: An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.

Abstract: A natural language text is received from a user. The natural language text includes typing characteristics metadata. An emotive content of the natural language text is determined using a machine learning model. The natural language text is modified based on the emotive content.

Abstract: A natural language text is received from a user. The natural language text includes typing characteristics metadata. An emotive content of the natural language text is determined using a machine learning model. The natural language text is modified based on the emotive content.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of a natural language content is generated by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value of at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. A reasoning operation is performed on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.

Abstract: Mechanisms are provided for processing natural language text. The natural language text is parsed to generate a logical parse which is then analyzed to identify a solicitation node of the logical parse for which a user is able to provide additional data to assist in processing the natural language text. A clarifying question is output to a computing device associated with a user based on content of the solicitation node and a response to the clarifying question is received from the user. The natural language text is then processed based on the response to the clarifying question received from the user to thereby generate a result. The result of the processing of the natural language text is output to a source of the natural language text.

Abstract: An approach is provided in which identifying a plurality of sections included in a Portable Document Format (PDF) file with each section being at a unique set of coordinate positions. At least one of the sections is identified as being a graphic image. The graphic image section is converted to a meaningful textual representations using a conversion process. An output document is then generated that includes the meaningful textual representation.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. Natural language content is received, upon which a reasoning operation is to be performed. A first parse representation of the natural language content is generated, by a parser, by performing natural language processing on the natural language content. A logical parse of the first parse is generated by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content. A reasoning operation on the logical parse is executed to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of the natural language content is generated by identifying latent logical terms within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value associated with at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. The propagating of the at least one knowledge value generates transaction records in a transaction knowledgebase data structure. A reasoning operation is executed based on the transaction knowledgebase data structure.

Abstract: Mechanisms are provided for processing logical relationships in natural language content. A logical parse of a first parse of a natural language content is generated by identifying latent logical operators within the first parse indicative of logical relationships between elements of the natural language content. The logical parse comprises nodes and edges linking nodes. At least one knowledge value is associated with each node in the logical parse. The at least one knowledge value of at least a subset of the nodes in the logical parse is propagated to one or more other nodes in the logical parse based on propagation rules. A reasoning operation is performed on the logical parse to generate a knowledge output indicative of knowledge associated with one or more of the logical relationships between elements of the natural language content.

Abstract: An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.

Abstract: An approach is provided in which a number of sections from a sequence of characters included in a Portable Document Format (PDF) file are identified. Each of the identified sections includes a unique set of coordinate positions. The approach builds links between the sections based on a relative position of each of the sections in relation to the other sections along an axis. The approach repeatedly merges sections based on the links that were built to form increasingly larger sections until a final larger section is generated with the characters appearing in a manner consistent with human reading of the rendered PDF document rather than the placement of the characters found within the original PDF file.

Abstract: A mechanism is provided in a data processing system for categorizing a user providing a text input. The mechanism receives an input text written by a user and determines a set of features associated with the input text. The mechanism processes the input text and the set of features by a detection model. The detection model comprises a plurality of detectors corresponding to a plurality of categories. Each of the plurality of detectors determines whether the user fits a respective category based on the input text and the set of features. The mechanism categorizes the user into one or more of the plurality of categories based on a result of processing the input text and the set of features by the detection model.