Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving a source document, applying one or more pre-processes to the source document to produce contextual information representative of the structure and content of the source document, and transforming the source document, based on the contextual information, to generate a question-and-answer searchable document.

Abstract: Disclosed are methods, systems, devices, apparatus, media, and other implementations, including a method that includes obtaining a query set (e.g., a universal set of questions), performing a question-and-answer (Q-A) search on one or more documents using the query set to produce answer data responsive to one or more questions included in the query set, with the answer data characterizing concepts associated with the one or more documents, and deriving structured output information for the one or more documents based on the answer data produced in response to performing the Q-A search.

Abstract: An intelligent document system provides one or more users, who are recipients of documents, with a way to “interact” with the documents for example for the purpose of understanding the content of the documents, and taking appropriate action in response to receiving the documents. Interacting with one or more documents can include navigating the documents guided by semantic content of the documents, asking questions that are answered based on the content of the documents. In some examples, the documents are “dynamic” in that users can manipulate data in the document for example for multiple different views or analyses. In some examples, the documents are augmented semantics and ontology that will allow the user to accurately navigate the document and achieve the natural interfacing they desire.

Abstract: A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A unified contextual graph for use by the conversational system, the unified contextual graph comprising components based on database queries of the conversational system and a user dialog between a user and the conversational system. For each of a set of user utterances produced in a dialog with the conversational system, a semantic meaning representation is determined. The semantic meaning representations are converted to respective sentential concept graphs. The unified contextual graph is updated based on new sentential concept graphs while the dialog with the conversational system progresses.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving a source document, applying one or more pre-processes to the source document to produce contextual information representative of the structure and content of the source document, and transforming the source document, based on the contextual information, to generate a question-and-answer searchable document.

Abstract: Disclosed are methods, systems, devices, apparatus, media, and other implementations, including a method that includes receiving query data representative of a question relating to source content of one or more source documents, and causing a search of a data repository maintaining data portions relating to the one or more source documents to determine a set of multiple matches between the query data and the data portions. The method additionally includes identifying one or more concepts associated with the set of multiple matches, with at least one of the identified concepts being associated with at least some of the multiple matches and including different respective values associated those some of the multiple matches, obtaining disambiguation information relevant to the at least one of the identified concepts, and selecting at least one of the multiple matches based on the obtained disambiguation information.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document, and determining whether one or more pre-determined questions stored in a question-answer cache maintained at the local device matches the query data according to one or more matching criteria. The method further includes obtaining from the question-answer cache, in response to a determination that at least one of the pre-determined questions matches the query data received from the remote device, at least one answer data item, associated with at least one pre-determined question, corresponding to an answer to the question relating to the source content.

Abstract: Disclosed are implementations that include a method including obtaining at a local device, a question-and-answer data item representative of a question-and-answer pair relating to source content of a source document, with the question-and-answer data item being associated with question-and-answer history information representative of historical information and access information for the question-and-answer data item, and determining based on the question-and-answer history information whether to perform data refinement operations on the question-and-answer data item.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document of a repository of a plurality of source documents, with the source content being associated with transformed content accessible from the local device. The method further includes generating, in response to determination, at the local device, of a match between the query data and at least one portion of the transformed content, output data comprising one or more of a pointer to access, in the source document accessible from the remote device, at least one portion of the source document corresponding to the at least one portion of the transformed content, or a copy of the at least one portion of the source document.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving, at a local device from a remote device, query data representative of a question relating to source content of a source document, and determining whether one or more pre-determined questions stored in a question-answer cache maintained at the local device matches the query data according to one or more matching criteria. The method further includes obtaining from the question-answer cache, in response to a determination that at least one of the pre-determined questions matches the query data received from the remote device, at least one answer data item, associated with at least one pre-determined question, corresponding to an answer to the question relating to the source content.

Abstract: Disclosed are methods, systems, devices, apparatus, media, design structures, and other implementations, including a method that includes receiving a source document, applying one or more pre-processes to the source document to produce contextual information representative of the structure and content of the source document, and transforming the source document, based on the contextual information, to generate a question-and-answer searchable document.

Abstract: Embodiments provide a computer implemented method, in a data processing system including a processor and a memory including instructions which are executed by the processor to cause the processor to train an enhanced chatflow system, the method including: ingesting a corpus of information including at least one user input node corresponding to a user question and at least one variation for each user input node; for each user input node: designating the node as a class; storing the node in a dialog node repository; designating each of the at least one variations as training examples for the designated class; converting the classes and the training examples into feature vector representations; training one or more training classifiers using the one or more feature vector representations of the classes; and training classification objectives using the one or more feature vector representations of the training examples.

Abstract: A computer-implemented conversational system framework to perform tasks associated with a client request. A conversation application executing on a hardware processor provides application workflow orchestration, the conversation application receiving a client request and sending one or more application requests based on the application workflow orchestration. A conversation system executing on a hardware processor provides conversation workflow orchestration, the conversation system receiving the one or more application requests. The conversation application and the conversation system develop dialog context and store the dialog context in a memory device. The conversation application and the conversation system develop the dialog context by invoking at least one micro-service to perform tasks associated with the one or more application requests. The conversation application generates a response to the client request based on the developed dialog context.

Abstract: A system and method performs automated domain concept discovery and clustering using word embeddings by receiving a set of documents for natural language processing for a domain, representing a plurality of entries in the set of documents as continuous vectors in a high dimensional continuous space, applying a clustering algorithm based on a mutual information optimization criterion to form a set of clusters, associating each entry of the plurality of entries with each cluster in the set of clusters through formalizing an evidence based model of each cluster given each entry, calculating a mutual information metric between each entry and each cluster using the evidence based model, and identifying a nominal center of each cluster by maximizing the mutual information.

Abstract: A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A user input is received in a dialog between a user and the conversational system, the user input in a natural language. A domain trained semantic matcher is used to determine a set of entities and a user intent from the user input. One or more queries is generated to selected ones of a plurality of knowledge sources, the knowledge sources created from domain specific knowledge. The results from the one or more queries are ranked based on domain specific knowledge. A system response is presented in the dialog based on at least a highest ranked result from the plurality of knowledge sources.

Abstract: Methods and systems for generating output of a simulation model in a simulation system are described. In an example, a processor may retrieve observed output data from a memory. The observed output data may be generated based on a simulation operator of a simulation model. The processor may further optimize a generalization error of a distance measure between the observed output data and model output data. The model output data may be generated based on a high-fidelity operator. The processor may further determine a correction operator based on the optimized generalization error of the distance measure. The processor may further append the correction operator to the simulation operator to produce a supplemented operator. The processor may further generate supplemented output data by applying the simulation model with the supplemented operator on a set of inputs.

Abstract: A method, apparatus and computer program product for presenting a user interface for a conversational system is described. A unified semantic representation of conversational content between a user and conversational system is created as a contextual graph of concepts and relations. A set of subgraph components of the semantic contextual graph dynamically identified based on a current dialog activity. The identified set of subgraph components in a user interface as a set of graphical elements representing respective concepts and relations.

Abstract: A method, program product and computer system to predict utterances in a dialog system includes receiving a set of utterances associated with a dialog between a client device and a dialog system, mapping the utterances to vector representations of the utterances, and identifying at least one cluster to which the utterances belong from among a plurality of possible clusters. A next cluster is predicted based upon a conditional probability of the next cluster following a set of a predetermined number of previous clusters using a language model. A next utterance is predicted from among a plurality of possible utterances within the predicted next cluster.

Abstract: A method, apparatus and computer program product for creating a dialog system for web content is described. Knowledge is extracted from a target web application for the dialog system. The knowledge includes an organizational structure of the target web application and domain knowledge pertinent to the target web application. A deep learning process associates the domain knowledge with the organization structure of the target application. A plurality of knowledge sources of different respective types are created from the domain knowledge and the organizational structure. Each of the knowledge sources is used for providing answers to user queries to the dialog system. As part of the invention, a semantic matcher is provided to select among the answers provided by the plurality of knowledge sources for a best answer to a user query.

Abstract: An intelligent document system provides one or more users, who are recipients of documents, with a way to “interact” with the documents for example for the purpose of understanding the content of the documents, and taking appropriate action in response to receiving the documents. Interacting with one or more documents can include navigating the documents guided by semantic content of the documents, asking questions that are answered based on the content of the documents. In some examples, the documents are “dynamic” in that users can manipulate data in the document for example for multiple different views or analyses. In some examples, the documents are augmented semantics and ontology that will allow the user to accurately navigate the document and achieve the natural interfacing they desire.