1675 results about "Question answer" 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.

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.

The embodiment of the invention discloses an automatic question-answering system. According to the automatic question-answering system, a user interaction unit receives a question input by a user, a question analysis unit extracts keywords from the question input by the user and expands the keywords, then an information retrieval unit searches a frequently asked question bank for answers to the question according to the expanded keywords and returns the answers to related documents, and finally, according to answer extraction rules corresponding to the question type, an answer extraction unit extracts an answer according with the rules from the related documents returned by the information retrieval unit, and sends the extracted answer to the user interaction unit to be fed back to the user. Compared with an automatic question-answering system in the prior art, the automatic question-answering system can automatically expand the keywords and divide the types of the input questions, different types of questions correspond to different types, further answer search is carried out in the types, and the accuracy and diversity of answers are improved.

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 provides an implement method of an FAQ Chinese question answering system in the tourism field. The implement method comprises the steps of FAQ collection and organization, construction of a tourism field knowledge base, user query, question analysis, answer extraction and the like, thereby realizing the FAQ Chinese question answering system in the tourism field. The implement method constructs the tourism field knowledge base-field knowledge network with the help of the idea of ontology, utilizes the KDML language to define and describe the terms and the relations of the tourism field and realizes the integration of the tourism field knowledge network and a general knowledge base-knowledge network. The invention proposes a calculation method of similarity of tourism questions on the basis, the method realizes the calculation of the similarity of the questions with the help of the characteristics of the questions of the tourism field and the combination of morphological relations, the syntactic dependency relations and the field concept semantic relations in the questions, and the method further searches the related question from a candidate question set and extracts the answer of the question based on the similarity calculation. The test result of a Yunnan tourism FAQ question answering system proves that the method is feasible and has better effect.

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.

A knowledge-base system includes a processor, a database, and a matcher for matching questions of clients to answers in the database. The knowledge-base system can be administered by emails sent to the system. Question-answer entries can be added, deleted, and modified through the use of emails and/or other forms. The system can be accessed over a network or directly accessed with an administration computer. Questions and answers are separately indexed in the system to increase the accuracy of generated results. The generated response sent to the client can be modified based on the question asked, the results, and predefined templates. The system can also detect when the system receives a reply from a customer in response to sent results. Once a reply is detected, the email is forwarded to an alternate email address.

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 invention discloses a question-answer pair quality evaluation method including the steps of clustering input question-answer pairs according to question contents to obtain a cluster including questions with same or similar semantic meanings and answers to the questions; performing quality evaluation between the question-answer pairs and quality evaluation in the question-answer pairs to the cluster and respectively obtaining the quality evaluation result between the question-answer pairs and the quality evaluation result in the question-answer pairs; inosculating the quality evaluation result between the question-answer pairs and the quality evaluation result in the question-answer pairs and outputting the question-answer pairs with high quality. The invention also provides a question-answer pair quality evaluation system so as to realize more effective question-answer pair quality evaluation and improve the commonality of quality evaluation.

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.

The invention discloses an automatic question answering method and a system thereof. The automatic question answering method comprises the following steps: step A, the information of a question is acquired through the analysis of the question; step B, the query criterion is generated according to the analysis results of the question for retrieval by using the search engine in knowledge source, thus searching out the file collection relating to the query criterion; the file collection is divided into paragraph collections; step C, paragraph collections relating to the query criterion are retrieved in a centralized way from the paragraphs by using the paragraph retrieval method according to the file retrieval results; and the answer of the question is returned from the paragraph collections. The automatic question answering method and the system improve the accuracy of answers and the precision of returning correct results.

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 question answering system includes a question answering unit, an analysis unit, a tree structure generation unit, a feature extraction unit, an evaluation unit and a re-ranking unit. The question answering unit executes search processing based on an input question and acquires answer candidates to the question. The analysis unit executes syntactic analysis processing or syntactic and semantic analysis processing on a passage obtained as a result of the search processing. The tree structure generation unit generates a tree structure based on an analysis result. The feature extraction unit extracts a relation between a search word applied in the search processing and each acquired answer candidate as a feature corresponding to each answer candidate from the tree structure. The evaluation unit determines an evaluation value of each answer candidate based on the feature extracted. The re-ranking unit re-ranks the answer candidates based on the evaluation values.