Abstract: A first list that includes a first set of one or more concept terms may be obtained. The first set of one or more concept terms may be candidates for being conceptually related to a seed concept term. Prior to the obtaining, a first client computing device may provide a first plurality of individual characters and the seed concept term to a first user using the first client computing device. The first client computing device may prompt the first user to generate the first set of one or more concept terms that are conceptually related to the seed concept term using one or more of the first plurality of individual characters. In response to the obtaining, one or more particular categories to which each of the first set of one or more concept terms belongs to may be determined.

Abstract: An architecture for data analysis of geographic data and associated context data. The data analysis of the geographic data and the associated context data includes receiving a query and determining a data model to output information requested by the query. The data analysis of the geographic data and the associated context data also includes accessing the geographic data and the associated context data from a data repository, providing the geographic data and the associated context data as input to the data model, and generating output including the information in response to the query.

Abstract: A method includes receiving, at a mobile hub device, communications including location-specific risk data and a task assignment. The method also includes generating an output indicating dispatch coordinates. The dispatch coordinates identifying a dispatch location from which to dispatch, from the mobile hub device, one or more unmanned vehicles to perform a task of the task assignment.

Abstract: An engagement classifier for a group chatbot is trained by leveraging the implicit dataset generated by humans engaging in both direct messages as well as group conversations. Human-to-human direct messages are used as an approximate representation of the domain knowledge and expertise of each user. The decision to engage in a group conversation is assumed to be based on that domain knowledge. The knowledge representations and instances of engagements in group conversations yields an effective set of features and labels which can be used to model the engagement decision. The same transfer learning technique is used to generate a knowledge representation for the group chatbot. Given this representation of the domain knowledge of the chatbot, the classifier can predict whether it should engage in any particular group conversation.

Abstract: Mechanisms are provided for implementing a virtual corpus engine that receives an inquiry to be processed and analyzes the inquiry to extract one or more features of the inquiry. The virtual corpus engine selects a weight matrix associated with a virtual corpus based on the extracted one or more features of the inquiry. The virtual corpus comprises a plurality of actual corpora of information. The weight matrix comprises a separate weight value for each actual corpus in the plurality of actual corpora. The virtual corpus engine processes the inquiry using a set of selected actual corpora selected from the plurality of actual corpora based on the weight values in the weight matrix and receives results of the processing of the inquiry using the set of selected actual corpora. The virtual corpus engine outputs the results of the processing of the inquiry.

Abstract: Mechanisms are provided for implementing a virtual corpus engine that receives an inquiry to be processed and analyzes the inquiry to extract one or more features of the inquiry. The virtual corpus engine selects a weight matrix associated with a virtual corpus based on the extracted one or more features of the inquiry. The virtual corpus comprises a plurality of actual corpora of information. The weight matrix comprises a separate weight value for each actual corpus in the plurality of actual corpora. The virtual corpus engine processes the inquiry using a set of selected actual corpora selected from the plurality of actual corpora based on the weight values in the weight matrix and receives results of the processing of the inquiry using the set of selected actual corpora. The virtual corpus engine outputs the results of the processing of the inquiry.

Abstract: A method is disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

Abstract: A system, method, and computer-readable medium are disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

Abstract: A computer-implemented method for creating question-answer pairs is provided. The computer-implemented method includes leveraging domain specific resources including, at least one or more of lexicons, glossaries, or knowledge bases for constructing templates for creating the question-answer pairs. The computer implemented method further includes leveraging user experiences of a plurality of users for constructing templates. The computer implemented method further includes eliminating erroneous question-answer pairs based on templates specifications of a heuristic process of the constructed templates.

Abstract: A system, method, and computer-readable medium are disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

Abstract: A method is disclosed for identifying paraphrases in a natural language processing (NLP) system comprising: receiving a first phrase and a second phrase by a system; analyzing the first phrase and the second phrase to provide a semantic and structural hierarchical comparison assessment, the semantic and structural hierarchical comparison assessment having an associated semantic and structural hierarchical comparison assessment value; and determining whether the semantic and structural hierarchical comparison assessment value exceeds a predetermined paraphrase equivalency criteria; and, responsive to determining the semantic and structural hierarchical comparison assessment value exceeds the predetermined paraphrase equivalency criteria, classifying the second phrase as being a rewording of the first phrase.

Abstract: A method for controlled sharing, in a cognitive computing system having a memory and a processor, of content from a variety of content providers may include receiving, by the cognitive computing system, an inquiry, wherein the inquiry is directed to at least one content topic. The method may then include identifying, by the cognitive computing system, the at least one content topic, and determining that a cognitive component of the cognitive computing system managed by a content provider has access to a content repository addressing the at least one content topic. The method may further include distributing, by the cognitive computing system, the inquiry to the cognitive component. The method may additionally include receiving a response from the cognitive component.

Abstract: A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a first phrase and a second phrase, the first and second phrases being paraphrases of each other, convert the first phrase into a first logical form and the second phrase into a second logical form, generate a phrasal edit that includes a difference between the first logical form and the second logical form, convert the phrasal edit into a disjunctive logical form in two directions, and generate a first plurality of paraphrases of the first and second phrases based on the disjunctive logical form.

Abstract: A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a plurality of bidirectional disjunctive logical forms which include two directional disjunctions of differences between a first logical form of a first sentence and second logical form of a second sentence, realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentence, score each of the first plurality of paraphrases based on textual similarity between the first plurality of paraphrases and the first and second sentences, and prune the first plurality of paraphrases to generate a second plurality of paraphrases based on the scores of each of the first plurality of paraphrases.

Abstract: A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a first phrase and a second phrase, the first and second phrases being paraphrases of each other, convert the first phrase into a first logical form and the second phrase into a second logical form, generate a phrasal edit that includes a difference between the first logical form and the second logical form, convert the phrasal edit into a disjunctive logical form in two directions, and generate a first plurality of paraphrases of the first and second phrases based on the disjunctive logical form.

Abstract: A system includes a question answering system executed by a computer, a processor, and a memory coupled to the processor. The memory is encoded with instructions that when executed cause the processor to provide training for training the question answering system. The training system is configured to receive a plurality of bidirectional disjunctive logical forms which include two directional disjunctions of differences between a first logical form of a first sentence and second logical form of a second sentence, realize the plurality of bidirectional disjunctive logical forms to generate a first plurality of paraphrases of the first and second sentence, score each of the first plurality of paraphrases based on textual similarity between the first plurality of paraphrases and the first and second sentences, and prune the first plurality of paraphrases to generate a second plurality of paraphrases based on the scores of each of the first plurality of paraphrases.

Abstract: Aspects of the present disclosure, in certain embodiments, are directed toward providing a visual representation of question quality in a question answering system. More particularly, aspects are directed toward receiving, by a question answering system, an input question having a set of query attributes. The set of query attributes may be user-influenced characteristics of the input question. Aspects of the present disclosure are also directed toward evaluating, by comparing the set of query attributes to a set of assessment criteria, the quality of the input question. Aspects of the present disclosure are also directed toward assigning, in response to evaluating the quality of the input question, a set of quality values to the set of query attributes. Using the assigned set of quality values and the set of query attributes, an icon that indicates a visual representation of the quality of the input question may be generated.

Abstract: A method, system and computer-usable medium are disclosed for using a contextual graph to summarize a corpus of content. Natural Language Processing (NLP) preprocessing operations are performed on text within an input corpus to form a grammatical analysis. In turn, the grammatical analysis is used to generate semantic associations between phrases in the input corpus. The resulting semantic associations are then used to determine the thematic relevance of the individual sentences in the input corpus to form a context-based ranking. In turn, the context-based ranking is used to construct a context graph, the vertices of which are represented by phrases, and the edges are represented by an aggregate score resulting from performing calculations associated with semantic similarity of the phrases. The resulting context graph is then used to generate a content summarization for the input corpus.

Abstract: A method, system and computer-usable medium are disclosed for generating a context-sensitive summarization of a corpus of content. Natural Language Processing (NLP) operations are performed on text within an input corpus to extract phrases, which are then used to generate a grammatical analysis. In turn, the grammatical analysis is used to determine the thematic relevance of individual sentences in the input corpus. Sentences within the input corpus are then ranked according to their respective thematic relevance. This ranking is used to construct a contextualized content graph, which in turn is used to generate a content summarization for the input corpus.

Abstract: A method, system and computer-usable medium are disclosed for using a contextual graph to summarize a corpus of content. Natural Language Processing (NLP) preprocessing operations are performed on text within an input corpus to form a grammatical analysis. In turn, the grammatical analysis is used to generate semantic associations between phrases in the input corpus. The resulting semantic associations are then used to determine the thematic relevance of the individual sentences in the input corpus to form a context-based ranking. In turn, the context-based ranking is used to construct a context graph, the vertices of which are represented by phrases, and the edges are represented by an aggregate score resulting from performing calculations associated with semantic similarity of the phrases. The resulting context graph is then used to generate a content summarization for the input corpus.