2078 results about "Question answering" patented technology

An intelligent home automation system answers questions of a user speaking “natural language” located in a home. The system is connected to, and may carry out the user's commands to control, any circuit, object, or system in the home. The system can answer questions by accessing the Internet. Using a transducer that “hears” human pulses, the system may be able to identify, announce and keep track of anyone entering or staying in the home or participating in a conversation, including announcing their identity in advance. The system may interrupt a conversation to implement specific commands and resume the conversation after implementation. The system may have extensible memory structures for term, phrase, relation and knowledge, question answering routines and a parser analyzer that uses transformational grammar and a modified three hypothesis analysis. The parser analyzer can be dormant unless spoken to. The system has emergency modes for prioritization of commands.

An evidence evaluation method and system based on question answering converts a report of analyzed information and / or a model of information into a collection of questions, determines answers for the collection of questions. A fact in the report is marked as being supported if one or more of the answers for the collection of questions support the fact. A fact in the report of analyzed facts is marked as being refuted if one or more of the answers for the collection of questions refute the fact. The method and system also may collect the answers as evidence and add the evidence to the model of information to create an updated model of information. The steps may be repeated using the updated report and updated model.

A method for regulating the asking and motivating the answering of questions via a computer network. The number and complexity of questions asked is controlled by a question regulation method, and the number and quality of answers provided is controlled by an answer evaluation method. The question regulation method permits users to post more numerous or more complex questions based on factors such as viewing of advertising, or provision of marketing information. The answer measurement method may be used to reward those who supply numerous or high-quality answers with premiums, public recognition, or employment opportunities.

A computer-implemented system and method provides authoritative answers, developed within a community-based question answering service to users of a general network information search. This community-based question answering service receives a question from a first user, and receives answers from community members regarding this question. The authority of the answer is then determined by members of the community and if the authority is of an acceptable level, the question together with its authoritative answer is added to a database which includes all authoritatively answered questions. The answering service has an interface that exposes the contents of this database to queries from users of the network who are not necessarily members of the answering service. In one embodiment, results from queries of the community-based database are integrated with queries of a second database of general network information. An improved general information search service is also provided that includes query results from the authoritative answers generated by the community-based answering service.

The disclosed subject matter consists of a system, a website, and their supporting methods for user-interactive question answering. The system consists of a pattern database to store question / answer patterns for users to select when asking / answering questions. Each question pattern may include or be associated with an answer pattern. The system also includes an asking unit to let the users ask questions with or without question patterns and processes users' questions. The system also includes an answering unit to let the users answer questions with or without answer patterns. The invented method and system can significantly improve users' questioning and answering efficiency and also help machines improve the accuracy of processing the questions and answers and accumulate useful knowledge.

Creating training data for a natural language processing system may comprise obtaining natural language input, the natural language input annotated with one or more important phrases; and generating training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases. In another aspect, a classifier may be trained based on the generated training instances. The classifier may be used to predict one or more potential important phrases in a query.

A question answering system includes a question input unit, a search unit, an answer candidate extraction unit, an answer candidate inspection unit and an answer output unit. The search unit executes search processing based on an input question. The answer candidate extraction unit extracts an initial answer candidate based on a result of the search processing. The answer candidate inspection unit inspects the initial answer candidate. The answer candidate inspection unit executes search processing with using a query including the initial answer candidate. The answer candidate inspection unit determines whether each word of a sentence obtained as a result of the search processing has a similar lexical meaning to that of each word of the input question. The answer candidate inspection unit selects an initial answer candidate contained in a query determined to have the similar lexical meaning, as a secondary answer candidate.

A system and method for automatic question answering is provided. Wherein the system includes: a user inputting module configured to receive question information; a question analyzing module configured to analyze the question information, and determine a set of keywords, a question type and a user intention type corresponding to the question information; a syntax retrieving and ranking module configured to retrieve, in a question and answer library and a category tree, answer candidates based on the question information, the set of keywords, the question type and the user intention type, determine a retrieval relevance between each of the answer candidates and the question information and rank the answer candidates according to the retrieval relevance, each of the answer candidates having a sequence number; and an outputting module configured to output an answer candidate ranked a specified sequence number. By using the application, lower costs for collection and improve successful rate of answers are provided by the system for automatic question answering.

The invention discloses a mapping knowledge domain questioning and answering system and method based on a template matching technique. The system comprises an offline module and an online module, wherein the offline module is mainly used for offline data preparation, and the online module is mainly used for system service. The system can support a friendly natural language question of a user to serve as a query, grammatical analysis is conducted on the question of the user, an offline-defined manual template library is searched for a matched question template according to a result obtained through grammatical analysis, a final structurized mapping knowledge domain query statement is generated according to an entity matching method and a relation matching method, retrieving is conducted in a mapping knowledge domain according to the structurized query statement, and then a final result is returned. According to the mapping knowledge domain questioning and answering system and method based on the template matching technique, the precise retrieving result can be given for the question of the user, and the searching satisfaction degree of the user is improved.

An approach is provided for generating actionable content ingestion recommendations based on an interaction history that is mined to extract interaction context parameters from questions and answer results that meet specified answer deficiency criteria by searching one or more content sources using the extracted interaction context parameters to identify new content that is relevant to improving the first answer, and then presenting the new content in an actionable content ingestion recommendation list for display and review by a domain expert, where the actionable content ingestion recommendation list recommends the new content for ingestion in a knowledge base corpus.

Embodiments of a multimodal question answering (mQA) system are presented to answer a question about the content of an image. In embodiments, the model comprises four components: a Long Short-Term Memory (LSTM) component to extract the question representation; a Convolutional Neural Network (CNN) component to extract the visual representation; an LSTM component for storing the linguistic context in an answer, and a fusing component to combine the information from the first three components and generate the answer. A Freestyle Multilingual Image Question Answering (FM-IQA) dataset was constructed to train and evaluate embodiments of the mQA model. The quality of the generated answers of the mQA model on this dataset is evaluated by human judges through a Turing Test.

A system is described in which a user can add one or more automated agents as “friends” in a social network service. In operation, an automated agent observes an information need expressed by the user via the social network service, e.g., in the form of an original message posted to the social network service; determines whether it is appropriate to reply to the information need; uses automated functionality to generate a reply message to the information need (if it is deemed appropriate to reply to the information need); and sends the reply message to a target destination, such as a social network page associated with the user. For example, without limitation, one type of automated agent performs a question-answering function. Another type of automated agent performs a social referral service.

Disclosed are systems, methods and computer-readable media for controlling a computing device to provide contextual responses to user inputs. The method comprises receiving a user input, generating a set of features characterizing an association between the user input and a conversation context based on at least a semantic and syntactic analysis of user inputs and system responses, determining with a data-driven machine learning approach whether the user input begins a new topic or is associated with a previous conversation context and if the received question is associated with the existing topic, then generating a response to the user input using information associated with the user input and any previous user input associated with the existing topic.

The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and / or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility. In this manner, the accuracy of answers to questions can be balanced with the cost of information extraction and analysis to compose the answers.

The present invention relates to a semi-automatic construction method for knowledge base of an encyclopedia question answering system, in which concept-oriented systematic templates are designed and important fact information related to entries is automatically extracted from summary information and body of the encyclopedia to semi-automatically construct the knowledge base of the encyclopedia question answering system. A semi-automatic construction method for knowledge base of an encyclopedia question answering system of the present invention comprises the steps of: (a) designing structure of the knowledge base with a plurality of templates for each entry and a plurality attributes related to each of the templates; (b) extracting structured information including the entry, an attribute name and attribute values from summary information of the encyclopedia; (c) extracting unstructured information including an attribute name and attribute values of the entry from a body of the encyclopedia; and (d) storing the structured information and the unstructured information in corresponding template and attribute of the knowledge base according to the entry.

Systems and methods for answering user questions using databases annotated with answerable questions are disclosed. The database includes database items organized into columns. Each of the columns may have a question annotated thereto. The question is a parameterized question that is answerable by the database items in the column. A question answering algorithm is used to search the database for an annotated question corresponding to a question that needs to be answered.

A question answering system includes an answer candidate extraction unit, a query generation unit, a passage search unit, an answer candidate inspection unit and an answer output unit. The answer candidate extraction unit executes a search process based on an input question to extract a plurality of initial answer candidates. The query generation unit generates a query including at least two of the initial answer candidates as search words. The passage search unit executes a search process based on the query to extract a hit sentence corresponding to the query. The answer candidate inspection unit analyzes the hit sentence to inspect a relationship between the initial answer candidates and generates answer candidates to the input question on a basis of an inspection result. The answer output unit outputs the answer candidates generated by the answer candidate inspection unit.

The invention discloses a Chinese question-answering system based on a neural network, which comprises a user interface module, a question word pre-segmentation module, a nerve cell pre-tagging module, a learning and training module, a nerve cell knowledge base module, a semantic block identification module, a question set index module and an answer reasoning module. The system comprises the steps of: firstly adopting an SIE encoding mode to encode the in-vocabulary words of the semantic block according to corresponding position, later converting an identification problem of the question semantic block into a tagging classification problem, and then adopting a classification model based on the neural network to determine the semantic structure of the question, and finally combing the semantic structure of the question to realize the question similarity computation based on the neural network and comparing the weight of various semantic features of the question by extracting the tagged semantic features of the question, thereby providing a basis for final answer reasoning. The Chinese question-answering system integrates the syntax, the semantics and the contextual knowledge of the question and can simulate the process that human beings process the sentence.

The invention relates to a deep learning-based question and answer matching method. The method comprises the following steps of: 1) sufficiently learning word orders and sentence local features of a question text and an answer text by utilizing two underlying deep neural networks: a long short-term memory network LSTM and a convolutional neural network CNN; and 2) selecting a keyword with best semantic matching on the basis of a pooling manner of an attention mechanism AM. Compared with existing methods, the method has the advantages of being in low in feature engineering workload, strong in cross-field performance and relatively high in correctness, and can be effectively applied to the fields of commercial intelligent customer service robots, automatic driving, internet medical treatment, online forum and community question answering.

Corpus analysis methods have previously been applied to text, typically to annotated text. The invention shows how to apply corpus analysis methods to information captured in databases, where the database columns include a mixture of both structured domains and unstructured domains containing text. It uses case-based methods to automatically organize cases for periodic review. The invention can help to identify opportunities for increasing knowledge about databases. By organizing a database around common lexical, semantic, pragmatic and syntactic relationships, the invention can be used to increase the effectiveness of previous corpus analysis methods, and to apply them to a diversity of commercial applications. The invention applies contextual constraints to focus the application of linguistic methods. This invention can provide a component for medical records, enterprise databases, information retrieval, question answering systems, interactive robots, interactive appliances, linguistically competent speech recognition, speech understanding and many other useful devices and applications that require a high level of linguistic competence within operational contexts.

Provided are systems and methods related to converting unlabeled data into structured and labeled data for answering one or more single-entity-single-relation questions. The systems and methods automates the labeling of data to generate training data for machine learning. The systems and methods identify and import question and answer pairs from an user generated discussion platform and access a knowledge base questions to extract questions by supervised extraction. The extracted questions are further filtered to remove mislabeled questions. When a question is posed, it is parsed for entity and relation, and an answer is identified by searching through the knowledge base.

A question sentence input part of question-answering system inputs a question sentence presented in a natural language. A document retrieval part of the system extracts a keyword from the question sentence and retrieves and extracts the document data including the keyword from a document database. An answer candidate extracting part of the system extracts a language presentation possibly becoming the answer as an answer candidate from the retrieved and extracted document data. An answer type determination part of the system determines an answer type of the answer candidate. An answer table output part of the system classifies the answer candidates by answer type and outputs an answer table listing all or part of the answer candidates having a predetermined evaluation or greater for each answer type in a table format.

The invention provides a question and answer method based on a knowledge graph, and an agricultural encyclopedia question and answer system. A natural language question raised by a user can be automatically analyzed; a topological structure based on a syntax tree is formed; retrieval and comparison are carried out through the topological structure and a question template in a grammar library; according to a mapping relation between the topological structure and a predicate nominatum, and a mapping relation between a synonym set and a relation or an attribute in the knowledge graph, a question-mapped predicate is obtained; in combination with an entity identified in the question, a final structured knowledge graph query statement is generated; retrieval is carried out in the knowledge graphaccording to the query statement; and a final result is returned. When the relevant topological structure cannot be retrieved in a question template library, the question answering is carried out bycalling common question-answer pairs of an FAQ question library. The question and answer system can give accurate answer retrieval for the question posed by the user, so that the satisfaction degree of the user to the agricultural encyclopedia question retrieval is improved.

The subject invention relates to a system and / or methodology that facilitate converting structured data (e.g., tabular information) into natural language, thus making it available to question answering systems and search engines. More specifically, the system and method employ the vast quantities of natural language on the particular storage system, database, network, or server that a user wishes to search. For example, the system can utilize natural-language based information located on the Web to assist in the task of converting structured data into natural language. In particular, the system can find at least one sentence or sentence fragment on the Web that refers to at least one tuple (e.g., row) in a given table. Following, those sentences can be generalized across all or substantially all tuples in the table. The resulting body of text can be used by the question answering system to answer user queries.

The embodiment of the invention provides an intelligent question-answer implementing method and system. The method comprises receiving a question to be queried; performing semantic analysis on the question; according to the result of the semantic analysis, performing corresponding retrieval treatment on the question, wherein the retrieval treatment comprises retrieval treatment on the question by at least one of a semantic relation digging system, a text library retrieving system, a knowledge base retrieving system and a question-answer library retrieving system; feeding an answer back according to the result of the retrieval treatment. The intelligent question-answer implementing method effectively improve the accuracy of question answering.

The present application relates to an intelligent question answering method, apparatus, computer device and storage medium. The method comprises the following steps of: acquiring question text of a target domain and extracting a target entity from the question text; obtaining The word vector of the target entity by using the pre-constructed word vector model. inputting The word vector into the pre-trained user intention classification model, and acquiring the user intention types of the question text. Generating A structured query statement according to the user intention type and the target entity, and finding the matching question answers from the knowledge base of the target domain according to the structured query statement. The method realizes intelligent question answering based on natural language processing technology and database technology, which can effectively improve the accuracy of question text matching with the answers in the knowledge base, and improve the accuracy ofintelligent question answering.

The present invention discloses an intelligent interactive question-answering system, which includes a knowledge module used to provide information for the user to query; an interactive module used for information interaction between the system and the user; and a processing module used for searching the answering information in knowledge module according to the question of the user; the knowledge module includes a question classification base used to store the question information and a knowledge base used to store the answering information; the processing module includes a semantic analysis module used to analyze the natural language for the problem of the user to generate query conditions; an information searching module used to search in the knowledge base according to the query condition; and a result generation module used to generate answers according to the searching results. The present invention discloses a question-answering processing method of an intelligent interactive question-answering system simultaneously. The present invention provides a rapid and simple system and method for obtaining the demanded information, so as to improve the processing ability for problems and the processing accuracy.

A question answering system estimates an answer type of an answer from a input question statement, extracts keywords from the question statement and retrieves a document database, extracts language expressions (answer candidates) from the extracted document data, assigns evaluation points thereto. When there are a plurality of answer candidates having the same language expression, the system sorts those evaluation points in descending ranking order of evaluation, calculates values of evaluation points using such weighting that the value to be processed for each evaluation point diminishes, regards the sum total of those values as the evaluation point of the answer candidate, and outputs the answer candidate whose counted evaluation point is equal to or greater than a predetermined evaluation as an answer.

A system and method for inferring informational goals and preferred level of details in answers in response to questions posed to computer-based information retrieval or question-answering systems is provided. The system includes a query subsystem that can receive an input query and extrinsic data associated with the query and which can output an answer to the query, and / or rephrased queries or sample queries. The query subsystem accesses an inference model to retrieve conditional probabilities that certain informational goals are present. One application of the system includes determining a user's likely informational goals and then accessing a knowledge data store to retrieve responsive information. The system includes a natural language processor that parses queries into observable linguistic features and embedded semantic components that can be employed to retrieve the conditional probabilities from the inference model. The inference model is built by employing supervised learning and statistical analysis on a set of queries suitable to be presented to a question-answering system. Such a set of queries can be manipulated to produce different inference models based on demographic and / or localized linguistic data.