Dong Wan

Bio: Dong Wan is an academic researcher. The author has contributed to research in topics: Question answering & Entity–relationship model. The author has an hindex of 1, co-authored 3 publications receiving 5 citations.

Intelligent question-answering method and device based on knowledge graph

Abstract: The embodiment of the invention provides an intelligent question-answering method and device based on a knowledge graph. The intelligent question-answering method comprises the steps: receiving a userquestion transmitted by a client, and respectively carrying out the entity recognition and intention recognition; and generating a knowledge graph query statement according to the entity identification result and the intention identification result, searching in a knowledge graph database to obtain an answer corresponding to the user question, and returning the answer to the client, wherein the knowledge graph database comprises entity names, entity attribute information and entity relationship information. The intelligent question-answering method and device based on a knowledge graph generates knowledge graph query statement after entity identification and intention identification are carried out based on a user question, and carries out searching in the knowledge graph database containing the entity name, the entity attribute information and the entity relation information to obtain the answer corresponding to the user question and return the answer to the client, thus achieving intelligent automatic answering of the user question, and improving the answering efficiency and accuracy.

The Intelligent Diagnostic System for Common Diseases using the Optimized Medical Knowledge Graph

Abstract: With the development of artificial intelligence technology, Clinical Decision Support System (CDSS) has been widely used. This paper presents a CDSS system, which called the Intelligent Auxiliary Diagnostic System for Common Disease (CD-IADS). CD-IADS assists the primary doctors in the diagnosis of common diseases with the patient's symptoms, signs, tests and personal background, which improves the primary doctors' working efficiency and reduces their misdiagnosis rate. In CD-IADS, medical experts construct the Medical Knowledge Graph according to medical literature and clinical experience firstly. Then, information entropy and particle swarm optimization (PSO) algorithms are used to optimize the special weights based on medical records. The system combines the advantages of the medical expert system and the artificial intelligence algorithm to support the diagnosis of common diseases. The paper takes the common diseases of the respiratory department as an example, and the TOP-1 and TOP-3 diagnostic accuracy rates are up to 64.6% and 86.0% respectively.

Information question-answering method and system

Abstract: The invention provides an information question-answering method and system. The method comprises the steps that a current question of a user and the last question of the user before the current question are acquired, it is judged whether or not the intention of the current question is the same as the last question, and if yes, additional information required for the intention is acquired; it is judged whether or not the additional information exists in a response returned from the last question and in the last question, and if yes, a response corresponding to the combination of the additionalinformation and the current question is acquired from a pre-constructed knowledge base according to the response returned from the last question and the additional information in the last question andthe current question; the response is returned to a client-side of the user. On one hand, the additional information required by the intension of the user is acquired according to contextual information to give the response according to the additional information and the current question, thereby making the response result more accurate; on the other hand, information question-answering is assisted by artificial intelligence, so that the time and labor are saved.

Question and answer method and device based on dictionary tree, recognition equipment and readable storage medium

Abstract: The invention is applicable to the technical field of natural language processing, and provides a question-answering method and device based on a dictionary tree, recognition equipment and a readablestorage medium. Inputting the inquiry information into a preset dictionary tree to obtain a first entity of the inquiry information; inputting the first entity into a preset knowledge graph to obtaina second entity corresponding to the first entity; and generating answer information according to the second entity, and returning the answer information to the user. Visibly, the problem that in theprior art, due to the fact that many name calling modes of alias names of entities exist, a question-answering system in the prior art cannot well recognize user input can be solved, and the effect that a user can be accurately replied in the question-answering process is achieved.

An Emergency Rescue System Architecture Based on Metaverse

Abstract: The imperfect staffing in pre-hospital first aid and the unreasonable dispatching of ambulances pose a threat to the life and health of the public. In order to solve the above problems, this paper proposes an emergency rescue system based on metaverse, which adds the function of personal doctor on the basis of the shared vehicle scheduling system based on blockchain. Metaverse is the fusion and interaction between the virtual and the real world, with blockchain, smart contracts, and other main technologies. Through the combination of metaverse and intelligent doctor assistant, the function and use process of personal doctor are designed. This paper also proposes an insurance-like payment mechanism, which is based on the premise of controlling the packing order of transactions in the blockchain by controlling the level of Gas Price and solving the problem of who pays and how to pay the transaction fee of the system. It not only ensures the normal operation of emergency rescue activities but also protects the interests of each node in the blockchain.

An Emergency Rescue System Architecture Based on Metaverse

Abstract: The imperfect staffing in pre-hospital first aid and the unreasonable dispatching of ambulances pose a threat to the life and health of the public. In order to solve the above problems, this paper proposes an emergency rescue system based on metaverse, which adds the function of personal doctor on the basis of the shared vehicle scheduling system based on blockchain. Metaverse is the fusion and interaction between the virtual and the real world, with blockchain, smart contracts, and other main technologies. Through the combination of metaverse and intelligent doctor assistant, the function and use process of personal doctor are designed. This paper also proposes an insurance-like payment mechanism, which is based on the premise of controlling the packing order of transactions in the blockchain by controlling the level of Gas Price and solving the problem of who pays and how to pay the transaction fee of the system. It not only ensures the normal operation of emergency rescue activities but also protects the interests of each node in the blockchain.

Query feedback method and device, computer equipment and storage medium

Abstract: The invention relates to a query feedback method and device, computer equipment and a storage medium. The method comprises the steps of performing semantic feature recognition on a query statement toobtain a recognition result of the query statement, wherein the recognition result comprises an original semantic entity and semantic information; obtaining at least two candidate semantic entities based on an identification result of the query statement; screening out a target semantic entity from the at least two candidate semantic entities; sending a feedback result corresponding to the targetsemantic entity to the terminal. According to the scheme, the candidate semantic entities are jointly queried by combining the original semantic entities and the semantic information on the basis of an artificial intelligence technology, so that the sources of the subsequently determined target semantic entities are wider, the diversity of the target semantic entities is improved, the diversity offeedback results is further improved, and the purpose of improving the feedback effect is achieved.

Question and answer method and apparatus based on knowledge graph

Abstract: A question and answer method and apparatus based on a knowledge graph, relating to the technical field of information processing. The problem that a terminal cannot query, in a knowledge graph, the result of a natural query statement not having a complete semantic meaning is solved. The question and answer method comprises: after obtaining a first natural query statement comprising a first query entity and first entity feature information, a terminal queries a first result from a knowledge graph according to the first query entity and the first entity feature information; after outputting the first result, the terminal obtains a second natural query statement; the terminal determines a missing part of the second natural query statement according to the first query entity or the first entity feature information; and the terminal queries a second result from the knowledge graph according to the missing part of the second natural query statement, and outputs the second result.