CN117541275A - Intelligent terminal commodity sales management system based on cloud technology - Google Patents
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Abstract
The invention relates to the field of commodity consultation information processing, in particular to an intelligent terminal commodity sales management system based on a cloud technology.
Description
Technical Field
The invention relates to the field of commodity consultation information processing, in particular to an intelligent terminal commodity sales management system based on a cloud technology.
Background
With the development of computer technology and internet technology, online commodity sales are becoming more mature, users can complete online purchases through intelligent terminals, such as computers or mobile phones, but a large number of clients access commodity sales platform consultation also brings pressure to customer service end reply processing, and with the development of semantic analysis technology, part of sales platforms adopt an automatic reply mode, and related technologies are generated.
For example, chinese patent publication No.: CN107609058A discloses a marketing method, a robot customer service end, a manual customer service end and a user end, and receives a session message sent by the user end; generating a user tag based on the session message and prestored historical consumption information of the user terminal; determining a sales label matching the user label; sending a request message for establishing session connection with the user terminal to at least one manual customer service terminal associated with the sales label; receiving a feedback message sent by the at least one artificial customer service side based on the request message; determining a target artificial customer service end based on at least one artificial customer service end corresponding to the feedback message; and sending a session connection establishment instruction to the target artificial customer service end. According to the embodiment of the invention, the target artificial customer service end is determined, so that the target artificial customer service end can sell goods or services to the user end, and the selling success rate is improved.
However, the prior art has the following problems,
in the prior art, due to the diversity of the client side consultation information, the perception of the real intention of the client side is not clear by adopting a label triggering mode, part of the consultation information does not contain a preset label, the expressed semantics are fuzzy, and the matching degree of the information automatically fed back by the client side is not high.
Disclosure of Invention
Therefore, the invention provides an intelligent terminal commodity sales management system based on a cloud technology, which is used for solving the problems that in the prior art, due to the diversity of client side consultation information, the perception of real intention of a client side is not clear by adopting a label triggering mode, part of consultation information does not contain preset labels, expressed semantics are fuzzy, and the matching degree of information automatically fed back by a customer service side is not high.
In order to achieve the above object, the present invention provides an intelligent terminal commodity sales management system based on cloud technology, which includes:
the data acquisition module is used for receiving interaction data issued by the intelligent terminal on the transaction platform;
the cloud storage module is used for storing a plurality of sample sentences, and each sample sentence comprises preset commodity keywords;
the cloud feedback module is respectively connected with the data acquisition module and the cloud storage module and used for selecting and enabling a direct feedback unit or an analysis feedback unit according to whether commodity keywords exist in the interaction data;
the direct feedback unit is used for determining commodity keywords in the interaction data and pushing commodity information associated with the commodity keywords to the intelligent terminal;
the analysis feedback unit is used for dividing sentences of the interactive data, screening sample sentences according to sentence structures of the obtained sentences, calculating association consistency coefficients according to association degrees of standard keywords in the screened sample sentences and commodity keywords, dividing consistency categories of the interactive data, pushing commodity information to an intelligent terminal, comprising,
selecting optimal associated commodity keywords based on the association degree ranking of the keywords in the strong-consistency interaction data and commodity keywords in the screened sample sentences, and pushing commodity information associated with the optimal associated commodity keywords to the intelligent terminal;
and constructing a data characterization set based on the association degree between the keywords in the weakly consistent interaction data, determining fuzzy commodity keywords based on the association degree between the keywords in the data characterization set and commodity keywords in the screened sample sentences, and pushing commodity information associated with the fuzzy commodity keywords to the intelligent terminal.
Further, the cloud feedback module selects to enable a direct feedback unit or an analysis feedback unit, wherein,
if commodity keywords exist in the interaction data, selecting and starting a direct feedback unit;
and if the commodity keywords do not exist in the interactive data, selecting to start an analysis feedback unit.
Further, the analysis feedback unit compares the sentence structure of each sentence with each sample sentence to screen the sample sentences, wherein,
and if the sentence structure of the sample sentence is the same as that of any sentence, the analysis feedback unit screens out the sample sentence.
Further, the analysis feedback unit is further configured to determine standard keywords in the filtered sample sentence, including,
if the keywords are both appeared in the interactive data and the filtered sample sentences, the analysis feedback unit judges that the keywords are standard keywords.
Further, the analysis feedback unit calculates the correlation consistency coefficient according to the formula (1),
，
in the formula (1), K represents a correlation consistency coefficient, pi represents an average value of the correlation degree of the ith commodity keyword and each standard keyword, P0 represents an average value of the correlation degree, n represents the number of commodity keywords which are included in calculation, i is an integer greater than 0, and the correlation degree of the commodity keywords and the standard keywords is the occurrence probability of the standard keywords under the condition that the commodity keywords appear in sample sentences of a cloud storage module.
Further, the analysis feedback unit compares the association consistency coefficient with a preset association consistency coefficient comparison threshold value,
if the association consistency coefficient is larger than a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is strong-consistency interaction data;
and if the association consistency coefficient is smaller than or equal to a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is weak-consistency interaction data.
Further, the analysis feedback unit selects the optimal associated commodity keywords, wherein,
and the analysis feedback unit calculates and sorts the association degree average value of each commodity keyword and each keyword in the interaction data, and determines the commodity keyword corresponding to the maximum association degree average value as the optimal association commodity keyword.
Further, the analysis feedback unit identifies a data characterization set according to the degree of association between the keywords,
the association degree between any keywords in the data representation set is larger than a preset fuzzy association threshold, and the association degree between the keywords is the probability of another keyword when the single keyword appears in the sample sentence of the cloud storage module.
Further, the analysis feedback unit identifies fuzzy keywords corresponding to each keyword in the data representation set, including,
the analysis feedback unit extracts keywords in the data representation set one by one, and calculates the keywords and each keyword
And determining the association degree of the commodity keywords, and determining the commodity keywords corresponding to the maximum association degree as fuzzy keywords corresponding to the keywords.
Further, the cloud storage module is further configured to store commodity information associated with each commodity keyword.
Compared with the prior art, the intelligent terminal transaction platform management system comprises a data acquisition module, a cloud storage module and a cloud feedback module, wherein the data acquisition module is used for receiving interaction data issued by the intelligent terminal on the transaction platform, the cloud storage module is used for storing sample sentences, a direct feedback unit in the cloud feedback module is used for directly pushing commodity information related to commodity keywords contained in the interaction data to the intelligent terminal, an analysis feedback unit is used for dividing consistency categories of the interaction data, selecting optimal related commodity keywords in strong consistency interaction data and pushing the related commodity information, and if the consistency interaction data are consistent, determining a plurality of fuzzy commodity keywords and pushing the related commodity information, the consistency categories of the interaction data are identified to represent whether semantic intention is clear or not, commodity information pushing logic is adjusted adaptively, accuracy of commodity information feedback to the intelligent terminal is guaranteed, and user experience is improved.
In particular, the analysis feedback unit calculates the association consistency coefficient, and divides the consistency category of the interaction data, the association degree of each commodity keyword and each standard keyword is considered in the calculation of the association consistency coefficient, and then the discreteness of the association degree of each keyword and each commodity keyword is represented, in the actual situation, the clear commodity keyword possibly does not exist in part of the interaction data sent by the user side, and the interaction data is subject to individual language habit, and the description of the interaction data is unclear, so that the association degree discreteness of each keyword and each commodity keyword is analyzed through the association consistency coefficient, the consistency of semantic intention in the interaction data is represented, and the analysis logic is recommended in the adjustment and recommendation of the follow-up adaptability, so that the accuracy of feeding back commodity information to the intelligent terminal is ensured, and the user experience is improved.
In particular, for strong consistency interaction data, the data characterization is clear, and the association degree of each keyword and fewer commodity keywords is high, so that the optimal associated commodity keywords are selected by considering the association degree of each keyword and the commodity keywords in the screened sample sentences in the case, commodity information is pushed to the intelligent terminal based on the optimal associated commodity keywords, the reliability is ensured, the accuracy of feeding back commodity information to the intelligent terminal is further ensured, and the user experience is improved.
In particular, for weak consistency interaction data, the data characterization is not clear, the association degree of each keyword and a plurality of commodity keywords is similar, and the overall semantic intention expressed by the interaction data is not clear, so that in the case, the association degree among the keywords in the interaction data needs to be analyzed, further, keywords with relatively strong consistency are identified, a data characterization set is constructed, a plurality of fuzzy commodity keywords are identified by taking the data characterization set as a technology, feedback information is output on the premise that the reliability is ensured as much as possible, the accuracy of feeding back commodity information to an intelligent terminal is ensured, and the user experience is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent terminal commodity sales management system based on cloud technology according to an embodiment of the invention;
fig. 2 is a schematic diagram of a cloud feedback module according to an embodiment of the invention;
FIG. 3 is a logic diagram of a feedback unit selection according to an embodiment of the invention
FIG. 4 is a logic diagram of classification of interaction data consistency in an embodiment of the invention.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the term "connected" should be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
Referring to fig. 1 to 4, fig. 1 is a schematic structural diagram of an intelligent terminal commodity sales management system based on cloud technology according to an embodiment of the present invention, fig. 2 is a schematic structural diagram of a cloud feedback module according to an embodiment of the present invention, fig. 3 is a logic diagram selected by a feedback unit according to an embodiment of the present invention, and fig. 4 is a logic diagram of classification of interaction data consistency according to an embodiment of the present invention. The intelligent terminal commodity sales management system based on cloud technology of the invention comprises:
the data acquisition module is used for receiving interaction data issued by the intelligent terminal on the transaction platform;
the cloud storage module is used for storing a plurality of sample sentences, and each sample sentence comprises preset commodity keywords;
the cloud feedback module is respectively connected with the data acquisition module and the cloud storage module and used for selecting and enabling a direct feedback unit or an analysis feedback unit according to whether commodity keywords exist in the interaction data;
the direct feedback unit is used for determining commodity keywords in the interaction data and pushing commodity information associated with the commodity keywords to the intelligent terminal;
the analysis feedback unit is used for dividing sentences of the interactive data, screening sample sentences according to sentence structures of the obtained sentences, calculating association consistency coefficients according to association degrees of standard keywords in the screened sample sentences and commodity keywords, dividing consistency categories of the interactive data, pushing commodity information to an intelligent terminal, comprising,
selecting optimal associated commodity keywords based on the association degree ranking of the keywords in the strong-consistency interaction data and commodity keywords in the screened sample sentences, and pushing commodity information associated with the optimal associated commodity keywords to the intelligent terminal;
and constructing a data characterization set based on the association degree between the keywords in the weakly consistent interaction data, determining fuzzy commodity keywords based on the association degree between the keywords in the data characterization set and commodity keywords in the screened sample sentences, and pushing commodity information associated with the fuzzy commodity keywords to the intelligent terminal.
Specifically, the specific structure of the data acquisition module is not limited, and the data acquisition module can be a virtual data receiving and transmitting end for establishing a communication protocol with the intelligent terminal, and of course, the data acquisition module can also be in other forms, and the detailed description is omitted.
Specifically, the specific structure of the cloud storage module is not limited, and the cloud storage module can be a cloud database, and only data can be stored, which is not described in detail.
Specifically, the specific structure of the cloud feedback module is not limited, and each unit in the cloud feedback module can be composed of a logic component, wherein the logic component comprises a field programmable part, a computer or a microprocessor.
Specifically, the method for obtaining the sample sentence is not limited, and the sample sentence can be obtained by crawling a plurality of corpus containing commodity keywords through a crawler program in advance and then screening, or can be in other forms, which are not described again.
Specifically, the method for obtaining the sentence structure is not limited, and the sentence structure of the sentence can be obtained by using a natural language tool, for example, a spaCy tool can be used to analyze the sentence structure and the syntax dependency of the sentence, and the sentence structure can include subjects, predicates, objects, targets, idioms, and the like, and of course, other natural language tools can also be used, which will not be repeated here.
Specifically, the cloud feedback module selects to enable a direct feedback unit or an analysis feedback unit, wherein,
if commodity keywords exist in the interaction data, selecting and starting a direct feedback unit;
and if the commodity keywords do not exist in the interactive data, selecting to start an analysis feedback unit.
Specifically, the analysis feedback unit compares the sentence structure of each sentence with each sample sentence to screen the sample sentences, wherein,
and if the sentence structure of the sample sentence is the same as that of any sentence, the analysis feedback unit screens out the sample sentence.
In particular, the analysis feedback unit is further configured to determine standard keywords in the filtered sample sentence, including,
if the keywords are both appeared in the interactive data and the filtered sample sentences, the analysis feedback unit judges that the keywords are standard keywords.
Specifically, the analysis feedback unit calculates the correlation consistency coefficient according to formula (1),
，
in the formula (1), K represents a correlation consistency coefficient, pi represents an average value of the correlation degree of the ith commodity keyword and each standard keyword, P0 represents an average value of the correlation degree, n represents the number of commodity keywords which are included in calculation, i is an integer greater than 0, and the correlation degree of the commodity keywords and the standard keywords is the occurrence probability of the standard keywords under the condition that the commodity keywords appear in sample sentences of a cloud storage module.
In particular, the analysis feedback unit compares the association consistency coefficient with a preset association consistency coefficient comparison threshold value,
if the association consistency coefficient is larger than a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is strong-consistency interaction data;
and if the association consistency coefficient is smaller than or equal to a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is weak-consistency interaction data.
Specifically, in this embodiment, the correlation consistency coefficient comparison threshold K0 is preset, in which a plurality of pieces of interaction data are extracted as samples in advance, the correlation consistency coefficient of each piece of interaction data is calculated, the average value Δk of the correlation consistency coefficients is solved, k0=a×Δkis set, a represents the precision offset coefficient, and 0.85 < a < 0.95.
Specifically, the analysis feedback unit calculates the association consistency coefficient, and divides the consistency category of the interaction data, the association degree of each commodity keyword and each standard keyword is considered in the calculation of the association consistency coefficient, and then the discreteness of the association degree of each keyword and each commodity keyword is represented, in the actual situation, the clear commodity keyword possibly does not exist in part of the interaction data sent by the user side and is limited by individual language habits, and the interaction data is not clearly described, so that the association degree discreteness of each keyword and each commodity keyword is analyzed through the association consistency coefficient, the consistency of semantic intention in the interaction data is represented, the analysis logic is recommended in the adjustment recommendation of the follow-up adaptability, further, the accuracy of feeding back commodity information to the intelligent terminal is guaranteed, and the user experience is improved.
Specifically, the analysis feedback unit selects the optimal associated commodity keywords, wherein,
and the analysis feedback unit calculates and sorts the association degree average value of each commodity keyword and each keyword in the interaction data, and determines the commodity keyword corresponding to the maximum association degree average value as the optimal association commodity keyword.
Specifically, the association degree of the commodity keywords and the keywords in the interaction data is the probability of the occurrence of the keywords under the condition of the occurrence of the commodity keywords in the sample sentences of the cloud storage module.
Specifically, for strong consistency interaction data, the data characterization is clear, and the association degree of each keyword and fewer commodity keywords is high, so that the optimal associated commodity keywords are selected by considering the association degree of each keyword and the commodity keywords in the screened sample sentences in the case, commodity information is pushed to the intelligent terminal based on the optimal associated commodity keywords, the reliability is ensured, the accuracy of feeding back commodity information to the intelligent terminal is further ensured, and the user experience is improved.
In particular, the analysis feedback unit identifies a data characterization set according to the association degree among the keywords,
the association degree between any keywords in the data representation set is larger than a preset fuzzy association threshold, and the association degree between the keywords is the probability of another keyword when the single keyword appears in the sample sentence of the cloud storage module.
Specifically, the association degree between keywords is the probability that a single keyword appears in a sample sentence of the cloud storage module when another keyword appears.
Specifically, the fuzzy association threshold Pe0 is a preset value in the present embodiment, wherein,
and obtaining a plurality of strong-consistency interaction data, solving an average value delta Pe of the association degree among keywords in the strong-consistency interaction data, and setting Pe0= delta Pe multiplied by beta, wherein beta represents an error coefficient, and 1.05 < beta < 1.15.
Specifically, the analysis feedback unit identifies fuzzy keywords corresponding to each keyword in the data representation set, including,
the analysis feedback unit extracts keywords in the data representation set one by one, and calculates the keywords and each keyword
And determining the association degree of the commodity keywords, and determining the commodity keywords corresponding to the maximum association degree as fuzzy keywords corresponding to the keywords.
Specifically, for weak consistency interaction data, the data characterization is ambiguous, the association degree of each keyword and a plurality of commodity keywords is similar, and the overall semantic intention expressed by the interaction data is ambiguous, so that in the case, the association degree among the keywords in the interaction data needs to be analyzed, further, keywords with relatively strong consistency are identified, a data characterization set is constructed, a plurality of fuzzy commodity keywords are identified by taking the data characterization set as a technology, feedback information is output on the premise that the reliability is ensured as much as possible, the accuracy of feeding back commodity information to an intelligent terminal is ensured, and the user experience is improved.
Specifically, the cloud storage module is further configured to store commodity information associated with each commodity keyword.
Specifically, the invention does not limit specific forms of commodity keywords and commodity information, the commodity keywords can be commodity names, and a person skilled in the art can set the form of commodity information according to specific needs, for example, the commodity information can include commodity selling links and store information of selling corresponding commodities, which is not described again.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
Claims (10)
1. An intelligent terminal commodity sales management system based on cloud technology, which is characterized by comprising:
the data acquisition module is used for receiving interaction data issued by the intelligent terminal on the transaction platform;
the cloud storage module is used for storing a plurality of sample sentences, and each sample sentence comprises preset commodity keywords;
the cloud feedback module is respectively connected with the data acquisition module and the cloud storage module and used for selecting and enabling a direct feedback unit or an analysis feedback unit according to whether commodity keywords exist in the interaction data;
the direct feedback unit is used for determining commodity keywords in the interaction data and pushing commodity information associated with the commodity keywords to the intelligent terminal;
the analysis feedback unit is used for dividing sentences of the interactive data, screening sample sentences according to sentence structures of the obtained sentences, calculating association consistency coefficients according to association degrees of standard keywords in the screened sample sentences and commodity keywords, dividing consistency categories of the interactive data, pushing commodity information to an intelligent terminal, comprising,
selecting optimal associated commodity keywords based on the association degree ranking of the keywords in the strong-consistency interaction data and commodity keywords in the screened sample sentences, and pushing commodity information associated with the optimal associated commodity keywords to the intelligent terminal;
and constructing a data characterization set based on the association degree between the keywords in the weakly consistent interaction data, determining fuzzy commodity keywords based on the association degree between the keywords in the data characterization set and commodity keywords in the screened sample sentences, and pushing commodity information associated with the fuzzy commodity keywords to the intelligent terminal.
2. The cloud technology based intelligent terminal commodity sales management system according to claim 1, wherein the cloud feedback module selects to enable a direct feedback unit or an analysis feedback unit, wherein,
if commodity keywords exist in the interaction data, selecting and starting a direct feedback unit;
and if the commodity keywords do not exist in the interactive data, selecting to start an analysis feedback unit.
3. The intelligent terminal commodity sales management system according to claim 1, wherein the analysis feedback unit compares the sentence structure of each sentence with each sample sentence to screen the sample sentences, wherein,
and if the sentence structure of the sample sentence is the same as that of any sentence, the analysis feedback unit screens out the sample sentence.
4. The cloud technology based intelligent terminal commodity sales management system according to claim 1, wherein said analysis feedback unit is further configured to determine standard keywords in the filtered sample sentences, comprising,
if the keywords are both appeared in the interactive data and the filtered sample sentences, the analysis feedback unit judges that the keywords are standard keywords.
5. The intelligent terminal commodity sales management system according to claim 1, wherein the analysis feedback unit calculates the correlation consistency coefficient according to formula (1),
，
in the formula (1), K represents a correlation consistency coefficient, pi represents an average value of the correlation degree of the ith commodity keyword and each standard keyword, P0 represents an average value of the correlation degree, n represents the number of commodity keywords which are included in calculation, i is an integer greater than 0, and the correlation degree of the commodity keywords and the standard keywords is the occurrence probability of the standard keywords under the condition that the commodity keywords appear in sample sentences of a cloud storage module.
6. The cloud technology based intelligent terminal commodity sales management system according to claim 1, wherein said analysis feedback unit compares said correlation consistency coefficient with a preset correlation consistency coefficient comparison threshold,
if the association consistency coefficient is larger than a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is strong-consistency interaction data;
and if the association consistency coefficient is smaller than or equal to a preset association consistency coefficient comparison threshold value, the analysis feedback unit judges that the interaction data is weak-consistency interaction data.
7. The cloud technology based intelligent terminal commodity sales management system according to claim 1, wherein the analysis feedback unit selects an optimal associated commodity keyword, wherein,
and the analysis feedback unit calculates and sorts the association degree average value of each commodity keyword and each keyword in the interaction data, and determines the commodity keyword corresponding to the maximum association degree average value as the optimal association commodity keyword.
8. The cloud technology-based intelligent terminal commodity sales management system according to claim 1, wherein the analysis feedback unit identifies a data characterization set according to the degree of association between the keywords,
the association degree between any keywords in the data representation set is larger than a preset fuzzy association threshold, and the association degree between the keywords is the probability of another keyword when the single keyword appears in the sample sentence of the cloud storage module.
9. The cloud technology based intelligent terminal commodity sales management system according to claim 1, wherein said analysis feedback unit identifies fuzzy keywords corresponding to each keyword in the data representation set, comprising,
the analysis feedback unit extracts keywords in the data representation set one by one, and calculates the keywords and each keyword
And determining the association degree of the commodity keywords, and determining the commodity keywords corresponding to the maximum association degree as fuzzy keywords corresponding to the keywords.
10. The cloud technology-based intelligent terminal commodity sales management system according to claim 1, wherein the cloud storage module is further configured to store commodity information associated with each commodity keyword.
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| JP2006277689A (en) * | 2005-03-30 | 2006-10-12 | Nec Fielding Ltd | Commodity sales management system, commodity information database server, and commodity sales management program |
| US10885550B1 (en) * | 2019-07-17 | 2021-01-05 | International Business Machines Corporation | Goods/service recommendation with data security |
| CN112102037A (en) * | 2020-09-16 | 2020-12-18 | 汤涛 | Live E-commerce platform commodity content intelligent pushing management system based on big data |
| CN113255323A (en) * | 2021-06-16 | 2021-08-13 | 明品云(北京)数据科技有限公司 | Description data processing method, system, electronic device and medium |
| CN113837824A (en) * | 2021-08-16 | 2021-12-24 | 上海漫集信息科技有限公司 | Information pushing method and system |
| CN113886708A (en) * | 2021-10-26 | 2022-01-04 | 平安银行股份有限公司 | Product recommendation method, device, equipment and storage medium based on user information |
| CN115082131A (en) * | 2022-07-26 | 2022-09-20 | 北京聚云数字信息技术有限公司 | Method and system for classified evaluation of advertisements based on specific standards |
| CN115659008A (en) * | 2022-09-27 | 2023-01-31 | 南京鼎山信息科技有限公司 | Information pushing system and method for big data information feedback, electronic device and medium |
| CN115689672A (en) * | 2022-09-29 | 2023-02-03 | 广州欢聚时代信息科技有限公司 | Chat type commodity shopping guide method and device, equipment and medium thereof |
| CN117319441A (en) * | 2023-09-27 | 2023-12-29 | 北京新知元浪网络科技有限公司 | Remote interaction method and system of meta universe |
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