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WO2018000205A1 - Procédé et système de réponse aux questions basés sur des intentions multiples et des paquets de compétences multiples, et robot - Google Patents

Procédé et système de réponse aux questions basés sur des intentions multiples et des paquets de compétences multiples, et robot Download PDF

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Publication number
WO2018000205A1
WO2018000205A1 PCT/CN2016/087517 CN2016087517W WO2018000205A1 WO 2018000205 A1 WO2018000205 A1 WO 2018000205A1 CN 2016087517 W CN2016087517 W CN 2016087517W WO 2018000205 A1 WO2018000205 A1 WO 2018000205A1
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WO
WIPO (PCT)
Prior art keywords
answer
question
skill
user
answers
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2016/087517
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English (en)
Chinese (zh)
Inventor
王昊奋
邱楠
杨新宇
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Gowild Robotics Co ltd
Original Assignee
Shenzhen Gowild Robotics Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Gowild Robotics Co ltd filed Critical Shenzhen Gowild Robotics Co ltd
Priority to CN201680001740.4A priority Critical patent/CN106462647A/zh
Priority to PCT/CN2016/087517 priority patent/WO2018000205A1/fr
Publication of WO2018000205A1 publication Critical patent/WO2018000205A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/903—Querying
    • G06F16/9032—Query formulation
    • G06F16/90332—Natural language query formulation or dialogue systems

Definitions

  • the invention relates to the field of robot interaction technology, in particular to a multi-intent multi-skilled question and answer method, system and robot.
  • a multi-intent based multi-skill package question and answer method including:
  • the step of answering the question information by using at least two skill packages specifically includes:
  • the step of obtaining the final answer from the answer set according to the user's intention specifically includes:
  • the step of answering the question information through the skill package specifically includes:
  • the step of answering the question information through the skill package specifically includes:
  • the step of obtaining the final answer from the answer set according to the user intention specifically includes:
  • the skill package includes at least a music skill package, a story skill package, a star technology package, and a horoscope skill package.
  • the invention discloses a multi-intent based multi-skill package question answering system, comprising:
  • An intention identification module configured to identify a user's intention according to the question information
  • the parsing module is configured to solve the question information by using at least two skill packages to obtain an answer set including at least two answers;
  • An output module for obtaining a final answer from the set of answers based on the user's intent.
  • the parsing module is further configured to: input the question information into at least two link data corresponding to the at least two skill packages for answering;
  • the output module is further configured to: associate the acquired at least two user intents by a relationship between the at least two link data, and select at least two of the acquired answer sets according to the association between the at least two user intents The answers are combined to get the final answer.
  • the parsing module is specifically configured to: segment the input question information;
  • the parsing module is specifically configured to:
  • the output module is specifically configured to:
  • the skill package includes at least a music skill package, a story skill package, a star technology package, and a horoscope skill package.
  • the present invention discloses a robot comprising a multi-intent based multi-skill package question answering system as described above.
  • the multi-skill package-based question and answer method disclosed by the present invention includes: obtaining question information; identifying user intention according to question information; and answering question information through at least two skill packs Get a set of answers that includes at least two answers; get the final answer from the set of answers based on the user's intent.
  • the user's question information can be answered by at least two skill packages, and then all the answers are obtained and then selected or associated according to the user's intention, thereby obtaining the final answer, wherein the association combination may be according to the user's intention.
  • the invention firstly proposes to manage the function modules of the robot and the robot in the management mode of the skill package. Under the framework of the parallel management, the processing speed and efficiency of the robot can be further improved, and the robot can realize the function more quickly and conveniently.
  • the startup improves the efficiency of the robot interaction with the user and the user's goodwill.
  • FIG. 1 is a flowchart of a multi-intent multi-skill packet question and answer method according to Embodiment 1 of the present invention
  • FIG. 2 is a schematic diagram of a multi-intent multi-skilled question answering system according to a second embodiment of the present invention.
  • Computer devices include user devices and network devices.
  • the user equipment or client includes However, it is not limited to computers, smart phones, PDAs, etc.; network devices include, but are not limited to, a single network server, a server group composed of a plurality of network servers, or a cloud-based cloud composed of a large number of computers or network servers.
  • the computer device can operate alone to carry out the invention, and can also access the network and implement the invention through interoperation with other computer devices in the network.
  • the network in which the computer device is located includes, but is not limited to, the Internet, a wide area network, a metropolitan area network, a local area network, a VPN network, and the like.
  • first means “first,” “second,” and the like may be used herein to describe the various elements, but the elements should not be limited by these terms, and the terms are used only to distinguish one element from another.
  • the term “and/or” used herein includes any and all combinations of one or more of the associated listed items. When a unit is referred to as being “connected” or “coupled” to another unit, it can be directly connected or coupled to the other unit, or an intermediate unit can be present.
  • a method for answering and answering based on a multi-skill package including:
  • the method for answering questions based on the multi-skill package includes: obtaining question information; identifying user intent according to the question information; answering the question information through at least two skill packages, and obtaining an answer set including at least two answers; The user intends to get the final answer from the answer set.
  • the user's question information can be answered by at least two skill packages, and then all the answers are obtained and then selected according to the user's intention, thereby obtaining the final answer, so that the obtained answer is more accurate, and by setting multiple skill packages. Can make the question and answer method more widely applicable.
  • the skill package includes at least a music skill package, a story skill package, a star technology package, and a horoscope skill package.
  • the user's questions can be more comprehensively queried and analyzed through different skill packages, and different answers are obtained, and then the answers are combined to obtain the final answer.
  • the first skill package, the second skill package, and the third skill package are included, and the answer set obtained from the three skill packages is compared with the user intention to obtain the final answer.
  • the first skill package may be a music skill package
  • the second skill package may be a story skill package
  • the third skill package may be a horoscope skill package.
  • the step of answering the question information by using at least two skill packages specifically includes:
  • the step of obtaining the final answer from the answer set according to the user's intention specifically includes:
  • the user asks for the message: "What time is it? Will it rain?” In this sentence, you need to use the time skill package and the weather skill package.
  • the answer needs to integrate these two skills packages. For composite intent, then multiple skill packs are required to be executed at the same time, and then combined according to the association between the intents.
  • the answer returned by each skill package is a partial answer. They know the intent to associate data between the links. Contact, and then through the partial answers obtained by each skill package to form a complete answer, according to the relationship between the intentions, the answers are combined and combined to get the complete answer. For example, in the above case, the robot's time skill package is now 9:00 am on June 20, 2016. The weather skill package is sunny today, then the robot will reply "now 9 am, today's weather is fine", thus The answers to each skill pack are summarized to get the final answer.
  • the step of obtaining the final answer from the answer set according to the user's intention specifically includes:
  • Each answer in the answer set is compared, and when each answer is complementary, all answers are merged into a final answer based on the user's intent.
  • the step of obtaining the final answer from the answer set according to the user's intention specifically includes:
  • the robot recognizes the user's intention according to the user's question, and then the system sends the user's question to the three skill packs according to the user's intention, and each skill pack sends the question to the question. Answer and then come up with a set of answers with three answers.
  • the percentage of similarity between the user's intention and the answer obtained by the first skill package is 60%
  • the similarity percentage of the answer obtained by the second skill package is 30%
  • the third skill package is obtained.
  • the percentage of similarity of the answer is 10%, then for these three answers, if the three answers are complementary, then the three answers will be merged to get the final answer; and if the three answers are Mutually exclusive, then choose the one with the highest similarity to the user's intention as the final answer. In this example, the answer from the first skill pack is selected as the final answer.
  • the step of answering the question information through the skill package specifically includes:
  • the step of answering the question information through the skill package specifically includes:
  • the user's question message is: Does Zhao Wei's movie look good?
  • the system analyzes the user's intention.
  • the system analyzes the user's intention to know whether Zhao Wei's movie is popular.
  • the system also divides the question information. For example, it is divided into Zhao Wei. , movie, then the system will query the link data, such as the knowledge base, after the query, for example, get the movie "to youth", judge the public's emotional tendency of the movie, whether to support the movie, or to deny the movie. If there is more support, then the movie is good-looking, otherwise it will not look good.
  • the user's question message is, is the bread delicious?
  • the system analyzes the user's intention.
  • the system analyzes the user's intention to know the taste of the bread, then the system will be divided into Bread, good or bad, then the system will check to judge the public's bias, whether you like bread, if you like more, you will say that the bread is delicious, otherwise it will not be good.
  • this embodiment discloses a multi-intent multi-skill package question answering system, including:
  • the obtaining module 201 is configured to obtain question information.
  • the intent identification module 202 is configured to identify the user's intention according to the question information
  • the parsing module 203 is configured to solve the question information by using at least two skill packages to obtain an answer set including at least two answers;
  • the output module 204 is configured to obtain a final answer from the set of answers according to the user's intention.
  • the user's question information can be answered by at least two skill packages, and then all the answers are obtained and then selected according to the user's intention, thereby obtaining the final answer, so that the obtained answer is more accurate, and by setting multiple skill packages. Can make the question and answer method more widely applicable.
  • the skill package includes at least a music skill package, a story skill package, a star technology package, and a horoscope skill package.
  • the user's questions can be more comprehensively queried and analyzed through different skill packages, and different answers are obtained, and then the answers are combined to obtain the final answer.
  • the parsing module is further configured to: input the question information into at least two link data corresponding to the at least two skill packages for answering;
  • the output module is further configured to: associate the acquired at least two user intents by a relationship between the at least two link data, and select at least two of the acquired answer sets according to the association between the at least two user intents The answers are combined to get the final answer.
  • the user asks for the message: "What time is it? Will it rain?” In this sentence, you need to use the time skill package and the weather skill package.
  • the answer needs to integrate these two skills packages. For composite intent, then multiple skill packs are required to be executed at the same time, and then combined according to the association between the intents.
  • the answer returned by each skill package is a partial answer. They know the intent to associate data between the links. Contact, and then through the partial answers obtained by each skill package to form a complete answer, according to the relationship between the intentions, the answers are combined and combined to get the complete answer. For example, in the above case, the robot's time skill package is now 9:00 am on June 20, 2016. The weather skill package is sunny today, then the robot will reply "now 9 am, today's weather is fine", thus The answers to each skill pack are summarized to get the final answer.
  • the output module is specifically configured to:
  • Each answer in the answer set is compared, and when each answer is complementary, all answers are merged into a final answer based on the user's intent.
  • the output module is specifically configured to:
  • the robot recognizes the user's intention according to the user's question, and then the system sends the user's question to the three skill packs according to the user's intention, and each skill pack sends the question to the question. Answer and then come up with a set of answers with three answers.
  • the percentage of similarity between the user's intention and the answer obtained by the first skill package is 60%
  • the similarity percentage of the answer obtained by the second skill package is 30%
  • the third skill package is obtained.
  • the percentage of similarity of the answer is 10%, then for these three answers, if the three answers are complementary, then the three answers will be merged to get the final answer; and if the three answers are Mutually exclusive, then choose the one with the highest similarity to the user's intention as the final answer. In this example, the answer from the first skill pack is selected as the final answer.
  • the parsing module is specifically configured to: segment the input question information
  • the parsing module is specifically configured to:
  • the user's question message is: Does Zhao Wei's movie look good?
  • the system analyzes the user's intention.
  • the system analyzes the user's intention to know whether Zhao Wei's movie is popular.
  • the system also divides the question information. For example, it is divided into Zhao Wei. , movie, then the system will query the link data, such as the knowledge base, after the query, for example, get the movie "to youth", judge the public's emotional tendency of the movie, whether to support the movie, or to deny the movie. If there is more support, then the movie is good-looking, otherwise it will not look good.
  • the user's question message is, is the bread delicious?
  • the system analyzes the user's intention.
  • the system analyzes the user's intention to know the taste of the bread, then the system will be divided into Bread, good or bad, then the system will check to judge the public's bias, whether you like bread, if you like more, you will say that the bread is delicious, otherwise it will not be good.
  • the embodiment further discloses a robot comprising a multi-intent based multi-skilled question answering system as described above.

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Artificial Intelligence (AREA)
  • Computational Linguistics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Mathematical Physics (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Machine Translation (AREA)
  • Manipulator (AREA)

Abstract

L'invention concerne un procédé de réponse aux questions basé sur des intentions multiples et des paquets de compétences multiples consistant à : obtenir une question (S101); reconnaître des intentions de l'utilisateur selon la question (S102); à répondre à la question au moyen d'au moins deux paquets d'adresse afin d'obtenir un ensemble de réponses comprenant au moins deux réponses (S103); et obtenir une réponse finale à partir du jeu de réponses selon les intentions de l'utilisateur (S104) Il est possible de répondre à une question d'un utilisateur au moyen d'au moins deux paquets d'adresse, puis la réponse finale est obtenue en sélectionnant, ou en associant et en combinant, toutes les réponses obtenues selon les intentions de l'utilisateur. L'association et la combinaison peuvent se référer à la combinaison, selon les intentions de l'utilisateur, des réponses obtenues à partir de multiples paquets d'adresse. Le procédé peut rendre la réponse plus précise et peut être appliqué plus largement.
PCT/CN2016/087517 2016-06-28 2016-06-28 Procédé et système de réponse aux questions basés sur des intentions multiples et des paquets de compétences multiples, et robot Ceased WO2018000205A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201680001740.4A CN106462647A (zh) 2016-06-28 2016-06-28 一种基于多意图的多技能包问答方法、系统和机器人
PCT/CN2016/087517 WO2018000205A1 (fr) 2016-06-28 2016-06-28 Procédé et système de réponse aux questions basés sur des intentions multiples et des paquets de compétences multiples, et robot

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CN109408800A (zh) * 2018-08-23 2019-03-01 优视科技（中国）有限公司 对话机器人系统及相关技能配置方法
WO2020109343A1 (fr) 2018-11-29 2020-06-04 F. Hoffmann-La Roche Ag Polythérapie pour le traitement de la dégénérescence maculaire
WO2020109344A1 (fr) 2018-11-29 2020-06-04 F. Hoffmann-La Roche Ag Dispositif d'administration oculaire pour oligonucléotides antisens
CN111710338A (zh) * 2020-06-28 2020-09-25 上海优扬新媒信息技术有限公司 一种话术播放方法及装置
US20220198292A1 (en) * 2020-12-21 2022-06-23 International Business Machines Corporation Automation of virtual assistant training
WO2023178192A1 (fr) 2022-03-15 2023-09-21 Compugen Ltd. Anticorps antagonistes de l'il-18bp et leur utilisation en monothérapie et polythérapie dans le traitement du cancer
CN116943244A (zh) * 2023-07-28 2023-10-27 广州银汉科技有限公司 一种多游戏玩家的自助服务系统
WO2025003753A1 (fr) 2023-06-26 2025-01-02 Compugen Ltd. Anticorps antagonistes d'il18-bp et leur utilisation en monothérapie et polythérapie dans le traitement du cancer

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CN109783733B (zh) * 2019-01-15 2020-11-06 腾讯科技（深圳）有限公司 用户画像生成装置及方法、信息处理装置及存储介质
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CN112784146A (zh) * 2019-11-04 2021-05-11 北京搜狗科技发展有限公司 一种数据处理方法、装置和用于数据处理的装置
CN112148848B (zh) * 2020-08-28 2024-12-10 出门问问创新科技有限公司 一种问答处理方法及装置
US12099816B2 (en) * 2021-01-20 2024-09-24 Oracle International Corporation Multi-factor modelling for natural language processing
CN113282727B (zh) * 2021-06-03 2024-04-16 北京捷通华声科技股份有限公司 问答处理方法、装置、计算机可读存储介质及处理器
CN114661885B (zh) * 2022-05-26 2022-10-11 深圳追一科技有限公司 问答处理方法、装置、计算机设备和存储介质

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* Cited by examiner, † Cited by third party
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CN109408800A (zh) * 2018-08-23 2019-03-01 优视科技（中国）有限公司 对话机器人系统及相关技能配置方法
CN109408800B (zh) * 2018-08-23 2024-03-01 阿里巴巴（中国）有限公司 对话机器人系统及相关技能配置方法
WO2020109343A1 (fr) 2018-11-29 2020-06-04 F. Hoffmann-La Roche Ag Polythérapie pour le traitement de la dégénérescence maculaire
WO2020109344A1 (fr) 2018-11-29 2020-06-04 F. Hoffmann-La Roche Ag Dispositif d'administration oculaire pour oligonucléotides antisens
CN111710338A (zh) * 2020-06-28 2020-09-25 上海优扬新媒信息技术有限公司 一种话术播放方法及装置
US20220198292A1 (en) * 2020-12-21 2022-06-23 International Business Machines Corporation Automation of virtual assistant training
WO2023178192A1 (fr) 2022-03-15 2023-09-21 Compugen Ltd. Anticorps antagonistes de l'il-18bp et leur utilisation en monothérapie et polythérapie dans le traitement du cancer
WO2025003753A1 (fr) 2023-06-26 2025-01-02 Compugen Ltd. Anticorps antagonistes d'il18-bp et leur utilisation en monothérapie et polythérapie dans le traitement du cancer
CN116943244A (zh) * 2023-07-28 2023-10-27 广州银汉科技有限公司 一种多游戏玩家的自助服务系统

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