Provided is a natural language query answering method. The natural language query answering method includes generating a query axiom from an input query, generating answer candidates from the input query, filtering the answer candidates based on a similarity between the query axiom and the answer candidates, reasoning out the answer candidates by using at least one of an inductive reasoning method, a deductive reasoning method, and an abductive reasoning method, calculating reliability of the answer candidates, determining ranks of the answer candidates based on the calculated reliability, and comparing a threshold value with a reliability ratio of reliability of an answer candidate determined as No. 1 rank to reliability of an answer candidate determined as No. 2 rank, readjusting the determined ranks according to a result of the comparison, and detecting a No. 1 rank answer candidate, determined through the readjustment, as a final answer.

A system and method for concept-based search and categorization that uses a lexical database to take a search term and from this to build a set of concepts and related terms and then searches stemmed or lemmatized text from a call transcription, email or chat message to perform categorization based on these concepts.

A non-transitory computer-readable recording medium stores a response processing program for causing a computer to execute processing including: receiving a question from a user input to a terminal; extracting, in a case where a plurality of pieces of answer candidate data that corresponds to the received question is retrieved, keywords or key phrases from the plurality of pieces of answer candidate data; classifying the extracted keywords or key phrases on the basis of words included in the keywords or key phrases; and outputting a classification result of the keywords or key phrases to the terminal in a state selectable by a user, together with a response text to the question.

The present application discloses an information processing method performed at a computing device. The method includes: collecting first information; executing an intent identification task on the first information to obtain an intent identification processing result; executing a slot identification task on the first information according to the intent identification processing result to obtain a slot identification processing result; narrowing a search range according to the slot identification processing result; and performing a database search for the first information within the narrowed search range.

Introduced here are various embodiments for selectively assigning a query to an expert. A network-accessible server system may receive a query from a client device indicating a question or project proposal. The query text may be parsed and attributes of the query may be determined by inspecting the parsed query text. The query attributes may be compared with attributes associated with a pool of experts with various specialties and expertise in various fields. The network-accessible server system may match the query attributes with attributes associated with a first expert with a similarity that exceeds a threshold similarity level to identify that an expertise of the first expert matches the requested expertise in the query. The first expert may be assigned to the query and prompted to provide a response to the query.

Aspects of this disclosure provide a device, system, and method for analyzing text. In an embodiment, a system is configured to convert characters of the text into a numerical time series signal. The numerical time series signal includes a time series conversion of the characters in numerical format. The system is further configured to generate a waveform with extracted information from the numerical time series signal. The extracted information having features based on politeness in language, a quantifiable use of punctuations, a quantifiable use of conjunctions, use of idioms, or a combination thereof. The system is additionally configured to determine whether the text is written by a specific user based on an analysis of the waveform against a threshold.

The present disclosure includes systems, apparatuses, and methods for event identification. In some aspects, a method includes receiving data including text and performing natural language processing on the received data to generate processed data that indicates one or more sentences. The method also includes generating, based on a first keyword set, a second keyword set having more keywords than the first keyword set. The method further includes, for each of the first and second keyword sets: detecting one or more keywords and one or more entities included in the processed data, determining one or more matched pairs based on the detected keywords and entities, and extracting a sentence, such as a single sentence or multiple sentences, from a document based on the one or more sentences indicated by the processed data. The method may also include outputting at least one extracted sentence.

An information search system, including: a database (12); a query sentence acceptance unit (26) that accepts a query sentence; an inputted search keyword extractor (44) that extracts an inputted search keyword from the query sentence; a shared keyword dictionary (30) in which relevant keywords are registered in association with each other; a local keyword dictionary (102) in which district keywords used in particular districts are registered; a candidate search keyword reader (32) that reads out a keyword that is relevant to the inputted search keyword; and a retrieval executor (40) that executes retrieval processing from the database using the inputted search keyword, wherein, in a case in which the inputted search keyword is not registered in the local keyword dictionary, the candidate search keyword reader refers to the shared keyword dictionary, so as to read out a keyword that is relevant to the inputted search keyword.

A business analytics conversational tool comprising: a device comprising a communication channel, a natural language processor (NLP), a fulfillment application program interface (F-API), a database application program interface (D-API), and a business management database; wherein: the NLP receives a user-input from a user through the communication channel; the NLP deduces an intent of the user-input; the NLP communicates the intent to the F-API; the F-API communicates a request for data associated with the intent to the database via the D-API; the D-API communicates the data associated with the intent to the F-API; the F-API converts the data associated with the intent to conversational form and sends the conversational form for voice output through the communication channel.

A system and method may analyze computer actions on a computer desktop system. Using a data gathering process, a low-level user action information item, describing input by a user (e.g. to the computer desktop system), may be received or gathered. The low-level user action information item may include an input type description and screen window information. Based on a series of low-level user action information items, a process a computer is engaging in with the user may be estimated or determined. The best or most appropriate next low-level user action may be displayed or suggested to the user, e.g. on a computer desktop system to a user.