CN116433318A - Intelligent vending machine system of commodity based on thing networking - Google Patents
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
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Abstract
The invention discloses an intelligent commodity vending machine system based on the Internet of things, which comprises: the first acquisition module is used for acquiring the shopping demand of the target consumer and determining commodity parameters according to the shopping demand; the recommending module is used for selecting a plurality of recommended commodities for the target consumer based on the commodity parameters and the expected price interval of the target consumer; the comparison module is used for acquiring serial number labels of each recommended commodity, scanning and comparing the serial number labels to screen out a plurality of recommended commodities with optimal cost performance; the generation module is used for generating commodity orders according to commodity information of the recommended commodity with the optimal cost performance selected by the target consumer and uploading the commodity orders to the vending machine for display and subsequent processing. The commodity parameters are determined, so that the commodity with high cost performance is recommended for selection, the commodity screening work one by one can be realized without manual work of consumers, the order generation efficiency and the subsequent processing efficiency are improved, and the shopping efficiency of users is indirectly improved.
Description
Technical Field
The invention relates to the technical field of the Internet of things, in particular to an intelligent commodity vending machine system based on the Internet of things.
Background
Under the wave of rapid development of science and technology, the human society gradually goes into an artificial intelligence era from an Internet era, and various industries gradually go to intellectualization. In the vending machine field, the application of third party payment mode has replaced traditional coin-operated vending machine, greatly reduced cost improves shopping efficiency. The existing automatic vending machine system workflow is used for acquiring a shopping list of a consumer to select corresponding commodities so as to generate a shopping order, and after the consumer finishes paying, the commodity discharging and distributing work is carried out, so that the experience of the consumer is greatly improved, however, the following problems exist in the method: the commodities in the shopping list can be generated after the user performs manual selection in advance, so that a great amount of time of the consumer is wasted for commodity selection work, and the selling efficiency and the experience of the customer are reduced.
Disclosure of Invention
Aiming at the problems displayed above, the invention provides an intelligent commodity vending machine system based on the Internet of things, which is used for solving the problems that in the background art, because commodities in a shopping list can be generated only after a user needs to manually select in advance, a great amount of time of a consumer is wasted for commodity selection work, and the vending efficiency and the experience of a customer are reduced.
An intelligent vending machine system for commodities based on the internet of things, the system comprising:
the first acquisition module is used for acquiring the shopping demand of the target consumer and determining commodity parameters according to the shopping demand;
the recommending module is used for selecting a plurality of recommended commodities for the target consumer based on the commodity parameters and the expected price interval of the target consumer;
the comparison module is used for acquiring serial number labels of each recommended commodity, scanning and comparing the serial number labels to screen out a plurality of recommended commodities with optimal cost performance;
the generation module is used for generating commodity orders according to commodity information of the recommended commodity with the optimal cost performance selected by the target consumer and uploading the commodity orders to the vending machine for display and subsequent processing.
Preferably, the first obtaining module includes:
the detection sub-module is used for detecting keywords input by a target consumer or uploaded reference images;
the analysis sub-module is used for analyzing part-of-speech characteristics of the keywords or collecting attribute characteristics of the reference image;
the first determining submodule is used for determining basic commodity characteristics of the commodity to be purchased of the target consumer according to the part-of-speech characteristics or the attribute characteristics;
and the acquisition sub-module is used for acquiring commodity parameters of the commodity according to the basic commodity characteristics of the commodity to be purchased.
Preferably, the recommendation module includes:
the screening sub-module is used for screening a first quantity of first commodities according to the commodity parameters and the expected price interval of the target consumer;
the invoking sub-module is used for invoking historical shopping information of the target consumer and determining the preference type of the target consumer for the purchased goods according to the historical shopping information;
the checking sub-module is used for removing the target first commodities, which do not accord with the preference type, of the first commodities to obtain a second number of second commodities;
and the scoring sub-module is used for determining a multi-dimensional evaluation index of the target consumer on the purchased goods according to the historical shopping information, scoring each second goods based on the multi-dimensional evaluation index, and determining the third goods with the evaluation score being greater than or equal to a preset score as the recommended goods.
Preferably, before the comparing module obtains the serial number label of each recommended commodity to scan and compare to screen out a plurality of recommended commodities with optimal cost performance, the system is further used for:
acquiring commodity text description information of each on-sale commodity;
determining a text feature sequence of each on-sale commodity according to the commodity text description information;
classifying each on-sale commodity according to the functional attribute of the commodity to obtain a classification result;
making labels of all the belonged commodity according to the text feature sequences of the plurality of the belonged commodity with the same function in the classification result, and obtaining a making result;
and setting a label model for each serial number label of the commodity on sale according to the formulated result.
Preferably, the comparison module includes:
the scanning sub-module is used for scanning the serial number label of each recommended commodity to obtain commodity characteristic information of the recommended commodity;
the analysis sub-module is used for analyzing a plurality of comparison items according to the functional information and the structural information of the commodity to be purchased of the target consumer;
the acquisition sub-module is used for acquiring attribute values of each comparison item of each recommended commodity according to commodity characteristic information of the recommended commodity;
and the comparison sub-module is used for comparing the attribute value of each comparison item of each first recommended commodity with the attribute value of each comparison item of other second recommended commodities, and screening out a plurality of recommended commodities with optimal cost performance according to comparison results.
Preferably, the generating module includes:
the second determining submodule is used for determining the using condition of the recommended commodity according to the commodity information of the target optimal cost performance;
a calling sub-module for calling the corresponding user information template based on the use condition;
the receiving sub-module is used for uploading the user information template to a target consumer mobile phone terminal and receiving filling content of the user information template on the user information template;
the verification sub-module is used for reliably verifying the shopping requirements of the target consumer based on the filling content;
and the generation sub-module is used for generating the commodity order according to the user information of the target consumer and the commodity information and the price information of the recommended commodity with the optimal cost performance of the target after the shopping demand of the target consumer passes the verification, and uploading the commodity order to the automatic vending machine for display and subsequent processing.
Preferably, the system further comprises:
the judging module is used for judging the completion progress of the commodity order according to the settlement information of the target consumer on the commodity order;
the second acquisition module is used for acquiring a distribution request of a target consumer when the completion progress of the commodity order is settlement completion;
the selecting module is used for selecting a delivery mode according to the delivery request and generating a delivery order;
and the delivery module is used for delivering the recommended commodity with the optimal cost performance of the target based on the delivery order.
Preferably, the evaluation module determines a multidimensional evaluation index of the target consumer for the purchased commodity according to the historical shopping information, specifically:
acquiring a plurality of historical consumption orders of a target consumer according to the historical shopping information;
determining the consumed goods of the target consumer and recommended goods of each consumed goods according to each historical consumption order;
evaluating a plurality of first recommendation factors according to the similarity of each consumed commodity and the recommended commodity;
determining the proportion of orders corresponding to the recommended commodity in the plurality of historical consumption orders, and determining the successful recommendation conversion rate of the recommended commodity according to the proportion;
screening a plurality of second recommendation factors based on the recommendation success conversion rate and the weight value of each first recommendation factor in the order corresponding to the recommended commodity;
and acquiring an evaluation index corresponding to the second recommendation factor as a multidimensional evaluation index of the target consumer for the purchased commodity.
Preferably, the determining the text feature sequence of each on-sale commodity according to the commodity text description information includes:
acquiring an initial text sequence of the on-sale commodity according to the commodity text description information;
carrying out structuring treatment on the initial text sequence to obtain an initial structured text sequence;
acquiring word characteristics of each text word in the structured text sequence;
and integrating word characteristics of each text word, and mapping the integrated word characteristics into the initial structured text sequence after integration so as to obtain a text characteristic sequence of the on-sale commodity.
Preferably, the analysis submodule analyzes a plurality of comparison items according to the function information and the structure information of the commodity to be purchased of the target consumer, and specifically includes:
determining basic functions and extended functions of the commodities to be purchased according to the function information of the commodities to be purchased, and determining basic structures and extended structures of the commodities to be purchased according to the structure information;
acquiring a preset number of functional element values and structural element values;
calculating the membership degree of each functional element value and each structural element value to the commodity to be purchased through a preset membership degree function;
determining the fitting degree of each functional element value and each structural element value to the commodity to be purchased according to the membership degree;
selecting a target functional element value and a target structural element value, the fitting degree of which is greater than or equal to a preset threshold value, as reference element values;
and acquiring the function item or the structure item corresponding to each target function element value and each target structure element value as the plurality of comparison items.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention.
Fig. 1 is a schematic structural diagram of an intelligent vending machine system for commodities based on the internet of things, which is provided by the invention;
fig. 2 is a schematic structural diagram of a first acquisition module in an intelligent vending machine system based on internet of things provided by the invention;
fig. 3 is a schematic structural diagram of a recommendation module in an intelligent vending machine system based on internet of things provided by the invention;
fig. 4 is a schematic structural diagram of a comparison module in the commodity intelligent vending machine system based on the internet of things.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
Under the wave of rapid development of science and technology, the human society gradually goes into an artificial intelligence era from an Internet era, and various industries gradually go to intellectualization. In the vending machine field, the application of third party payment mode has replaced traditional coin-operated vending machine, greatly reduced cost improves shopping efficiency. The existing automatic vending machine system workflow is used for acquiring a shopping list of a consumer to select corresponding commodities so as to generate a shopping order, and after the consumer finishes paying, the commodity discharging and distributing work is carried out, so that the experience of the consumer is greatly improved, however, the following problems exist in the method: the commodities in the shopping list can be generated after the user performs manual selection in advance, so that a great amount of time of the consumer is wasted for commodity selection work, and the selling efficiency and the experience of the customer are reduced. In order to solve the problems, the embodiment discloses an intelligent commodity vending machine system based on the Internet of things.
An intelligent vending machine system for commodities based on the internet of things, as shown in fig. 1, the system comprises:
a first obtaining module 101, configured to obtain a shopping requirement of a target consumer and determine a commodity parameter according to the shopping requirement;
a recommendation module 102, configured to select a plurality of recommended products for the target consumer based on the product parameters and a desired price interval of the target consumer;
the comparison module 103 is used for acquiring serial number labels of each recommended commodity, scanning and comparing the serial number labels to screen out a plurality of recommended commodities with optimal cost performance;
the generating module 104 is configured to generate a commodity order according to the commodity information of the recommended commodity with the optimal cost performance selected by the target consumer, and upload the commodity order to the vending machine for display and subsequent processing.
In this embodiment, the shopping demand is expressed as the type of merchandise that the target consumer needs to purchase, for example: food, household products, drinks, stationery products, etc.;
in this embodiment, the commodity parameter is specific commodity information of a certain type of commodity, for example: the food comprises: quick-frozen foods, cooked foods, snacks, and the like;
in this embodiment, the recommended commodity is represented as a specific commodity parameter, for example: quick-frozen dumplings, pork head meat, potato chips, instant noodles and the like;
in this embodiment, the serial number label of each recommended commodity is set in advance by the machine;
in the present embodiment, the commodity information is represented as manufacturer information, qualification information, component information, price information, and the like of the commodity.
The working principle of the technical scheme is as follows: firstly, acquiring shopping demands of target consumers through a first acquisition module, determining commodity parameters according to the shopping demands, selecting a plurality of recommended commodities for the target consumers through a recommendation module based on the commodity parameters and expected price intervals of the target consumers, acquiring serial number labels of each recommended commodity through a comparison module, scanning and comparing to screen out a plurality of recommended commodities with optimal cost performance, and finally, generating commodity orders according to commodity information of the recommended commodities with optimal cost performance of the target consumers selected through a generation module, and uploading the commodity orders to an automatic vending machine for display and subsequent processing.
The beneficial effects of the technical scheme are as follows: the commodity parameters are determined by analyzing the shopping demands of target consumers, so that the commodity parameters are recommended to the consumers for selection, the commodities can be screened one by one without manual selection of the consumers, the order generation efficiency and the subsequent processing efficiency are improved, the shopping efficiency of the users is indirectly improved, and the problems that in the prior art, the commodities in the shopping list are required to be manually selected by the users in advance and then the orders can be generated, so that a great amount of time of the consumers is wasted for commodity selection work, and the selling efficiency and the experience of the clients are reduced are solved.
In one embodiment, as shown in fig. 2, the first obtaining module 101 includes:
a detection sub-module 1011 for detecting a keyword or an uploaded reference image input by a target consumer;
a parsing sub-module 1012, configured to parse part-of-speech features of the keyword or collect attribute features of the reference image;
a first determining submodule 1013, configured to determine a basic commodity feature of the commodity to be purchased of the target consumer according to the part-of-speech feature or the attribute feature;
an acquisition sub-module 1014 is configured to acquire commodity parameters according to the basic commodity characteristics of the commodity to be purchased.
In this embodiment, the part-of-speech feature is represented as an input keyword being a verb or noun, where the verb may be manual. Nouns may be cooked foods or the like;
in this embodiment, the attribute features are represented as visual attribute features of a reference image, such as meat. Vegetarian food, etc.
The beneficial effects of the technical scheme are as follows: the commodity parameters of the commodity to be purchased of the target consumer can be obtained gradually from multiple angles, so that the follow-up recommended commodity meets the requirements of the target consumer, and the practicability and the stability are improved.
In one embodiment, as shown in fig. 3, the recommendation module 102 includes:
a screening submodule 1021 for screening a first quantity of first commodities according to the commodity parameters and the expected price interval of the target consumer;
a retrieving submodule 1022, configured to retrieve historical shopping information of the target consumer, and determine a preference type of the target consumer for the purchased commodity according to the historical shopping information;
an troubleshooting submodule 1023, configured to exclude the target first commodities, where the plurality of first commodities do not meet the preference type, to obtain a second number of second commodities;
1024, configured to determine a multi-dimensional evaluation index of the target consumer for the purchased goods according to the historical shopping information, score each second goods based on the multi-dimensional evaluation index, and confirm the third goods with the evaluation score being greater than or equal to a preset score as the recommended goods;
in the present embodiment, the above preference types include: good quality, low price, multiple functions, good practicability, large or small volume, etc.
The beneficial effects of the technical scheme are as follows: the second commodity meeting the demands of the target consumer can be screened out according to the expected price interval of the target consumer and the preference type of the second commodity for the historical purchasing commodity, reasonable recommended commodities can be accurately selected for the target consumer according to the price demands and the consumption habits of the target consumer, the experience of the consumer is improved, and further, the recommended commodities can be strictly checked in a finer manner by scoring the second commodity and screening out the third commodity, so that the finally reserved recommended products are more in accordance with the aesthetic and demands of the target consumer, and the practicability is further improved.
In this embodiment, the invoking sub-module determines, according to the historical shopping information, a preference type of the target consumer for the purchased commodity, including:
obtaining comment texts of target consumers for different historical purchased commodities according to the historical shopping information;
obtaining optimized use information and deteriorated use information of different historical purchased commodities for a target consumer from comment texts of the target consumer for the different historical purchased commodities;
according to the optimized use information and the deteriorated use information of different historical purchased commodities for the target consumer and the product characteristics of the historical purchased commodities, the emotion polarity of the target consumer for the different historical purchased commodities is estimated;
determining a correlation coefficient between the emotion tendency of the target consumer and the commodity type according to the emotion polarity of the target consumer for the commodities purchased in different histories and the commodity type of the commodities purchased in different histories;
screening a plurality of cardiometer commodity types of the target consumer according to the correlation coefficient between the emotion tendencies of the target consumer and the commodity types;
acquiring a plurality of keywords of each cardiometer commodity type, analyzing the semantics of the keywords, and constructing a commodity preference semantic matrix of a target consumer according to the analysis result;
determining the preference layering commodity class level of the target consumer according to the commodity preference semantic matrix of the target consumer;
determining high-level commodity class information according to the preference layering commodity class of the target consumer, and acquiring commodity label attributes corresponding to the high-level commodity class information;
the item tag attributes are parsed to determine the type of preference of the target consumer for the purchased item.
The beneficial effects of the technical scheme are as follows: the commodity type of the heart instrument can be intuitively and accurately determined according to the subjective consumption concept of the target consumer by analyzing the historical shopping information of the target consumer to determine the commodity type of the heart instrument, so that conditions are laid for subsequent commodity preference determination.
In one embodiment, before the comparing module obtains the serial number label of each recommended commodity to scan and compare to screen out the recommended commodity with the optimal cost performance, the system is further used for:
acquiring commodity text description information of each on-sale commodity;
determining a text feature sequence of each on-sale commodity according to the commodity text description information;
classifying each on-sale commodity according to the functional attribute of the commodity to obtain a classification result;
making labels of all the belonged commodity according to the text feature sequences of the plurality of the belonged commodity with the same function in the classification result, and obtaining a making result;
and setting a label model for each serial number label of the commodity on sale according to the formulated result.
In the present embodiment, the commodity text description information is represented as ingredient information and use information of the commodity, use information, and the like.
The beneficial effects of the technical scheme are as follows: through classifying functions of all the on-sale commodities and then formulating labels, the sequence labels of the on-sale commodities can be quickly searched for the functions of each on-sale commodity, so that the working efficiency is improved, and meanwhile, the practicability is further improved.
In one embodiment, as shown in fig. 4, the comparing module 103 includes:
a scanning sub-module 1031 for scanning serial number labels of each recommended commodity to obtain commodity characteristic information of the recommended commodity;
the analysis submodule 1032 is used for analyzing a plurality of comparison items according to the functional information and the structural information of the commodity to be purchased of the target consumer;
the collecting submodule 1033 is used for collecting attribute values of each comparison item of each recommended commodity according to commodity characteristic information of the recommended commodity;
and a comparison submodule 1034, configured to compare the attribute value of each comparison item of each first recommended commodity with the attribute value of each comparison item of other second recommended commodities, and screen out a plurality of recommended commodities with optimal cost performance according to the comparison result.
The beneficial effects of the technical scheme are as follows: the plurality of comparison items can be analyzed according to the functional information and the structural information of the commodity to be purchased of the target consumer, so that the emphasis option of the target consumer on purchasing the commodity can be quickly and accurately obtained, the recommended commodity with high cost performance can be reasonably selected for the target consumer, and the intellectualization and the practicability are improved.
In one embodiment, the generating module includes:
the second determining submodule is used for determining the using condition of the recommended commodity according to the commodity information of the target optimal cost performance;
a calling sub-module for calling the corresponding user information template based on the use condition;
the receiving sub-module is used for uploading the user information template to a target consumer mobile phone terminal and receiving filling content of the user information template on the user information template;
the verification sub-module is used for reliably verifying the shopping requirements of the target consumer based on the filling content;
and the generation sub-module is used for generating the commodity order according to the user information of the target consumer and the commodity information and the price information of the recommended commodity with the optimal cost performance of the target after the shopping demand of the target consumer passes the verification, and uploading the commodity order to the automatic vending machine for display and subsequent processing.
The beneficial effects of the technical scheme are as follows: by reliably verifying the user information of the target consumer, the target consumer can be ensured to have the condition of using the recommended commodity, and the stability is improved.
In one embodiment, the system further comprises:
the judging module is used for judging the completion progress of the commodity order according to the settlement information of the target consumer on the commodity order;
the second acquisition module is used for acquiring a distribution request of a target consumer when the completion progress of the commodity order is settlement completion;
the selecting module is used for selecting a delivery mode according to the delivery request and generating a delivery order;
and the delivery module is used for delivering the recommended commodity with the optimal cost performance of the target based on the delivery order.
The beneficial effects of the technical scheme are as follows: the distribution orders can be intelligently generated to carry out diversified distribution processing according to the distribution request of the target consumer, so that the experience and practicability of the consumer are further improved.
In one embodiment, the evaluation module determines a multi-dimensional evaluation index of the target consumer for the purchased commodity according to the historical shopping information, specifically:
acquiring a plurality of historical consumption orders of a target consumer according to the historical shopping information;
determining the consumed goods of the target consumer and recommended goods of each consumed goods according to each historical consumption order;
evaluating a plurality of first recommendation factors according to the similarity of each consumed commodity and the recommended commodity;
determining the proportion of orders corresponding to the recommended commodity in the plurality of historical consumption orders, and determining the successful recommendation conversion rate of the recommended commodity according to the proportion;
screening a plurality of second recommendation factors based on the recommendation success conversion rate and the weight value of each first recommendation factor in the order corresponding to the recommended commodity;
and acquiring an evaluation index corresponding to the second recommendation factor as a multidimensional evaluation index of the target consumer for the purchased commodity.
The beneficial effects of the technical scheme are as follows: by evaluating the recommendation factors according to the historical orders and screening the recommendation factors, the evaluation indexes corresponding to the preference commodities of the target consumers can be determined according to the standard samples, so that the final recommended commodities are more in line with the requirements of the target consumers, and the experience and practicability of the target consumers are further improved.
In one embodiment, the determining the text feature sequence of each on-sale commodity according to the commodity text description information comprises the following steps:
acquiring an initial text sequence of the on-sale commodity according to the commodity text description information;
carrying out structuring treatment on the initial text sequence to obtain an initial structured text sequence;
acquiring word characteristics of each text word in the structured text sequence;
and integrating word characteristics of each text word, and mapping the integrated word characteristics into the initial structured text sequence after integration so as to obtain a text characteristic sequence of the on-sale commodity.
The beneficial effects of the technical scheme are as follows: the conversion of the text description information of each commodity on sale to the text feature sequence can be completed orderly. The stability is improved.
In one embodiment, the analysis submodule analyzes a plurality of comparison items according to the functional information and the structural information of the commodity to be purchased of the target consumer, and specifically includes:
determining basic functions and extended functions of the commodities to be purchased according to the function information of the commodities to be purchased, and determining basic structures and extended structures of the commodities to be purchased according to the structure information;
acquiring a preset number of functional element values and structural element values;
calculating the membership degree of each functional element value and each structural element value to the commodity to be purchased through a preset membership degree function;
determining the fitting degree of each functional element value and each structural element value to the commodity to be purchased according to the membership degree;
selecting a target functional element value and a target structural element value, the fitting degree of which is greater than or equal to a preset threshold value, as reference element values;
and acquiring the function item or the structure item corresponding to each target function element value and each target structure element value as the plurality of comparison items.
The beneficial effects of the technical scheme are as follows: the method and the system can reasonably determine the expansion structure information and the expansion function information corresponding to the commodity to be purchased to generate the corresponding comparison item, so that the requirement of a target consumer is met, meanwhile, the screening condition of the recommended commodity is perfected, and the practicability is further improved.
It will be appreciated by those skilled in the art that the first and second aspects of the present invention refer to different phases of application.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. Intelligent vending machine system of commodity based on thing networking, its characterized in that, this system includes:
the first acquisition module is used for acquiring the shopping demand of the target consumer and determining commodity parameters according to the shopping demand;
the recommending module is used for selecting a plurality of recommended commodities for the target consumer based on the commodity parameters and the expected price interval of the target consumer;
the comparison module is used for acquiring serial number labels of each recommended commodity, scanning and comparing the serial number labels to screen out a plurality of recommended commodities with optimal cost performance;
the generation module is used for generating commodity orders according to commodity information of the recommended commodity with the optimal cost performance selected by the target consumer and uploading the commodity orders to the vending machine for display and subsequent processing.
2. The internet of things-based intelligent vending machine system of claim 1, wherein the first acquisition module comprises:
the detection sub-module is used for detecting keywords input by a target consumer or uploaded reference images;
the analysis sub-module is used for analyzing part-of-speech characteristics of the keywords or collecting attribute characteristics of the reference image;
the first determining submodule is used for determining basic commodity characteristics of the commodity to be purchased of the target consumer according to the part-of-speech characteristics or the attribute characteristics;
and the acquisition sub-module is used for acquiring commodity parameters of the commodity according to the basic commodity characteristics of the commodity to be purchased.
3. The internet of things-based intelligent vending machine system of claim 1, wherein the recommendation module comprises:
the screening sub-module is used for screening a first quantity of first commodities according to the commodity parameters and the expected price interval of the target consumer;
the invoking sub-module is used for invoking historical shopping information of the target consumer and determining the preference type of the target consumer for the purchased goods according to the historical shopping information;
the checking sub-module is used for removing the target first commodities, which do not accord with the preference type, of the first commodities to obtain a second number of second commodities;
and the scoring sub-module is used for determining a multi-dimensional evaluation index of the target consumer on the purchased goods according to the historical shopping information, scoring each second goods based on the multi-dimensional evaluation index, and determining the third goods with the evaluation score being greater than or equal to a preset score as the recommended goods.
4. The internet of things-based intelligent vending machine system of claim 1, wherein prior to the comparison module obtaining serial number tags for each recommended item for scanning and comparing to screen out a plurality of best cost performance recommended items, the system is further configured to:
acquiring commodity text description information of each on-sale commodity;
determining a text feature sequence of each on-sale commodity according to the commodity text description information;
classifying each on-sale commodity according to the functional attribute of the commodity to obtain a classification result;
making labels of all the belonged commodity according to the text feature sequences of the plurality of the belonged commodity with the same function in the classification result, and obtaining a making result;
and setting a label model for each serial number label of the commodity on sale according to the formulated result.
5. The internet of things-based intelligent vending machine system of claim 1, wherein the comparison module comprises:
the scanning sub-module is used for scanning the serial number label of each recommended commodity to obtain commodity characteristic information of the recommended commodity;
the analysis sub-module is used for analyzing a plurality of comparison items according to the functional information and the structural information of the commodity to be purchased of the target consumer;
the acquisition sub-module is used for acquiring attribute values of each comparison item of each recommended commodity according to commodity characteristic information of the recommended commodity;
and the comparison sub-module is used for comparing the attribute value of each comparison item of each first recommended commodity with the attribute value of each comparison item of other second recommended commodities, and screening out a plurality of recommended commodities with optimal cost performance according to comparison results.
6. The internet of things-based intelligent vending machine system of claim 1, wherein the generation module comprises:
the second determining submodule is used for determining the using condition of the recommended commodity according to the commodity information of the target optimal cost performance;
a calling sub-module for calling the corresponding user information template based on the use condition;
the receiving sub-module is used for uploading the user information template to a target consumer mobile phone terminal and receiving filling content of the user information template on the user information template;
the verification sub-module is used for reliably verifying the shopping requirements of the target consumer based on the filling content;
and the generation sub-module is used for generating the commodity order according to the user information of the target consumer and the commodity information and the price information of the recommended commodity with the optimal cost performance of the target after the shopping demand of the target consumer passes the verification, and uploading the commodity order to the automatic vending machine for display and subsequent processing.
7. The internet of things-based intelligent vending machine system of claim 1, wherein the system further comprises:
the judging module is used for judging the completion progress of the commodity order according to the settlement information of the target consumer on the commodity order;
the second acquisition module is used for acquiring a distribution request of a target consumer when the completion progress of the commodity order is settlement completion;
the selecting module is used for selecting a delivery mode according to the delivery request and generating a delivery order;
and the delivery module is used for delivering the recommended commodity with the optimal cost performance of the target based on the delivery order.
8. The intelligent vending machine system of claim 3, wherein the evaluation module determines a multi-dimensional evaluation index of the target consumer for the purchased commodity according to the historical shopping information, specifically:
acquiring a plurality of historical consumption orders of a target consumer according to the historical shopping information;
determining the consumed goods of the target consumer and recommended goods of each consumed goods according to each historical consumption order;
evaluating a plurality of first recommendation factors according to the similarity of each consumed commodity and the recommended commodity;
determining the proportion of orders corresponding to the recommended commodity in the plurality of historical consumption orders, and determining the successful recommendation conversion rate of the recommended commodity according to the proportion;
screening a plurality of second recommendation factors based on the recommendation success conversion rate and the weight value of each first recommendation factor in the order corresponding to the recommended commodity;
and acquiring an evaluation index corresponding to the second recommendation factor as a multidimensional evaluation index of the target consumer for the purchased commodity.
9. The intelligent vending machine system of claim 4, wherein the determining the text feature sequence of each on-sale commodity according to the commodity text description information comprises:
acquiring an initial text sequence of the on-sale commodity according to the commodity text description information;
carrying out structuring treatment on the initial text sequence to obtain an initial structured text sequence;
acquiring word characteristics of each text word in the structured text sequence;
and integrating word characteristics of each text word, and mapping the integrated word characteristics into the initial structured text sequence after integration so as to obtain a text characteristic sequence of the on-sale commodity.
10. The intelligent vending machine system of claim 5, wherein the analysis submodule analyzes a plurality of comparison items according to the functional information and the structural information of the commodity to be purchased of the target consumer, specifically:
determining basic functions and extended functions of the commodities to be purchased according to the function information of the commodities to be purchased, and determining basic structures and extended structures of the commodities to be purchased according to the structure information;
acquiring a preset number of functional element values and structural element values;
calculating the membership degree of each functional element value and each structural element value to the commodity to be purchased through a preset membership degree function;
determining the fitting degree of each functional element value and each structural element value to the commodity to be purchased according to the membership degree;
selecting a target functional element value and a target structural element value, the fitting degree of which is greater than or equal to a preset threshold value, as reference element values;
and acquiring the function item or the structure item corresponding to each target function element value and each target structure element value as the plurality of comparison items.
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