An apparatus and computer implemented method that include obtaining, into a computer, text of a patent, automatically finding and extracting, using the computer, a set of claim text from the patent text, identifying, using the computer, text of independent claims from the set of claim text, displaying in a first row on a computer monitor the text of the independent claims, automatically determining a plurality of preliminary scope-concept phrases from the text of the independent claims, displaying in a second row on the computer monitor the text of the plurality of preliminary scope-concept phrases, eliciting and receiving user input to specify a first one of the plurality of preliminary scope-concepts phrases, and highlighting each occurrence of the specified first one of the plurality of preliminary scope-concept phrases in a plurality of the independent claims displayed in the first row. A scope concept builder tool is also provided.

A method for dialog state tracking includes decoding, by a fertility decoder, encoded dialog information associated with a dialog to generate fertilities for generating dialog states of the dialog. Each dialog state includes one or more domains. Each domain includes one or more slots. Each slot includes one or more slot tokens. The method further includes generating an input sequence to a state decoder based on the fertilities. A total number of each slot token in the input sequence is based on a corresponding fertility. The method further includes encoding, by a state encoder, the input sequence to the state decoder, and decoding, by the state decoder, the encoded input sequence to generate a complete sequence of the dialog states.

Systems and methods are provided herein for enabling a computing system to search and interact with service records containing natural language text to aid in the analysis of those records by: displaying in a user interface an image of a complex system; receiving, from the user interface, a high-level selection of criteria of the complex system; querying issue maps associated with individual natural language service records of a corpus of natural language service records based on the high-level selection, wherein the issue maps specify at least one term related to the complex system and a location on the complex system associated with the at least one term; and returning at least one issue map, wherein the at least one issue map returned specifies a term or location correlated to the criteria of the complex system indicated by the high-level selection.

The present application discloses a method and an apparatus for information query, and an electronic device, which relates to a field of deep learning (DL), natural language processing (NLP) and artificial intelligence (AI) technology. The method includes: receiving a query sentence, segmenting the query sentence to obtain word segments, and obtaining a dependency relationship between two word segments and part of speech of the word segments; obtaining a coding sequence of the query sentence according to the dependency relationship and the part of speech of the word segments; matching the coding sequence with a generalized template to obtain a core corpus of the query sentence, wherein the generalized template comprises part of speech to be extracted and a dependency relationship to be extracted; and obtaining a query result corresponding to the query sentence based on the core corpus. The application no longer relies on the accumulation of massive business scenario data to enhance a generalization ability, which ensures accurate and efficient information query, and improves the efficiency and reliability of the information query process. At the same time, it may support information query in different business scenarios, with strong expansion capability and high universality.

A computer system includes memory storing computer-executable instructions and a processor configured to execute the computer-executable instructions. The computer-executable instructions include building a questions table including multiple first questions and multiple potential requirements to which the first questions correspond, respectively. The computer-executable instructions include adding, to the questions table, one or more second questions, each of which correspond to at least two requirements from among the potential requirements. The computer-executable instructions include adding, to the questions table, for each second question among the one or more second questions, the at least two requirements to which the second question corresponds. The computer-executable instructions include determining a question, from among the first questions and the second questions, that corresponds to a highest number of potential requirements, and displaying the determined question to a user.

The present application provides a robot response method, apparatus, device and storage medium. The method includes: obtaining, by a robot, current query voice; extracting semantic information of the current query voice; matching the semantic information of the current query voice with multiple semantic information clusters stored in advance to get a matched target semantic information cluster, where each semantic information cluster includes: at least one Q&A instance, and each Q&A instance includes: semantic information corresponding to a historical query voice and a query question selected in a query list corresponding to the historical query voice; and obtaining, by the robot, the number of times each query question was selected in the target semantic information cluster, determining, according to the number of times each query question was selected, a target query question corresponding to the current query voice, and outputting a query response corresponding to the target query question.

A dialogue generation method, a network training method and apparatus, a storage medium, and a device are provided. The method includes: predicting, based on a plurality of a plurality of pieces of candidate knowledge text in a first candidate knowledge set, a preliminary dialogue response of a first dialogue preceding text; processing the first dialogue preceding text based on the preliminary dialogue response to obtain a first dialogue preceding text vector; obtaining a piece of target knowledge text based on a probability value of the piece of target knowledge text of being selected to be used in generating a final dialogue response, the probability value being obtained based on the first dialogue preceding text vector; and generating the final dialogue response based on the first dialogue preceding text and the piece of target knowledge text.

Examples of the present disclosure describe systems and methods for enterprise search that leverage periodically updated user context of an enterprise user for intent understanding and treat a search session as a dialog between the user and a digital assistant to allow multi-modal interaction. For example, a query input by the user may be received from a client application having search functionality and an integrated assistant. A current state of the user context may be leveraged to understand the query. Based on the understanding, one or more responsive entities may be retrieved from an enterprise search index as results. Based on the results, a response may be generated that includes the results and a prompt to cause the user to further refine the query and/or provide feedback. The response may be provided to the client application for output as part of a search session dialog between the user and assistant.

Systems and methods for facilitating an enterprise user to obtain an answer to a user question within an enterprise based on an enterprise knowledge graph are provided. In particular, an enterprise server may receive the user question from the enterprise user, determine a suggested topic associated with the user question based on the enterprise knowledge graph by transforming the user question into a semantic representation to identify a plurality of similar entities within the enterprise knowledge graph, and determine whether a relevant question-and-answer (Q&A) pair linked to the suggested topic exists based on the enterprise knowledge graph. In response to a determination that the relevant Q&A pair does not exist, the enterprise server may determine a predicted answer to the user question and update the enterprise knowledge graph.

Systems and methods thereof, of generating a unique identification code for an industrial commodity. The method includes receiving a user query indicative of at least one constructional and operational characteristic of the commodity, inspecting the user query to determine whether the user query is complete for identification of the commodity, updating the user query based on the inspection, identifying at least one attribute of the commodity from the updated user query, based on a list of predefined attributes of the commodity, mapping the at least one attribute to at least one of predefined attribute types, predefined regional standards, predefined commodity rules, and predefined commodity types, and generating the unique identification code for the commodity, based on the mapping. The predefined attribute types may be a predefined commodity group and a predefined commodity part.