CN112966504A - Name identification and association recommendation method and device, computer equipment and storage medium - Google Patents

Name identification and association recommendation method and device, computer equipment and storage medium Download PDF

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CN112966504A
CN112966504A CN202110323354.XA CN202110323354A CN112966504A CN 112966504 A CN112966504 A CN 112966504A CN 202110323354 A CN202110323354 A CN 202110323354A CN 112966504 A CN112966504 A CN 112966504A
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accessory
name
information
association
user side
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CN112966504B (en
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马明信
吴宇
李静帆
柯康
王春媚
李攀
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Shenzhen One Account Technology Co ltd
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    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
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Abstract

The invention relates to big data technology, and discloses a name identification and association recommendation method, a device, computer equipment and a storage medium, wherein the name identification and association recommendation method comprises the following steps: acquiring an accessory name, identifying an associated name of the accessory name, summarizing the associated name to obtain an associated list, receiving the associated name selected by a user side and setting the associated name as a target name; acquiring at least one accessory information from a transaction system according to the target name, summarizing to form an accessory list, receiving the accessory information selected by the user side and setting the accessory information as transaction information; setting the accessory information selected by the user side as target information, acquiring accessory information having accessory association relation with the target information, summarizing to form a recommendation list, and setting the accessory information selected by the user side as transaction information; and summarizing the transaction information to form order information, and sending the order information to a transaction system. The invention avoids the problem of low transaction efficiency and accuracy caused by frequent communication with accessory merchants, and improves the efficiency of accessory transaction.

Description

Name identification and association recommendation method and device, computer equipment and storage medium
Technical Field
The invention relates to the technical field of data analysis of big data, in particular to a name recognition and association recommendation method and device, computer equipment and a storage medium.
Background
In the process of selecting accessories by a repair shop independently, the accessories need to be selected one by one, and in the process of selecting the accessories required by an accident vehicle, all the required accessories need to be selected for many times and then are sent to an accessory vendor or a professional accessory store.
However, after the inventor realizes that the accessory supplier or the platform receives the accessory appeal information of the repair shop, the accessory supplier or the platform can further communicate with the accessory supplier or the platform under the condition of disagreement with the accessory purchased before, because the accessory has various common names defined by each region, the accessory required by the repair shop and the corresponding accident vehicle type information need to be repeatedly confirmed, the accessory supplier or the platform distributes the required accessory through logistics after the confirmation is finished, and the repair shop can also repeatedly verify the required accessory; therefore, the current transaction operation of the vehicle accessory frequently communicates with the accessory dealer, so that the problem of low transaction efficiency and accuracy occurs.
Disclosure of Invention
The invention aims to provide a name identification and association recommendation method, device, computer equipment and storage medium, which are used for solving the problems of low transaction efficiency and low accuracy caused by frequent communication with an accessory provider in the prior art.
In order to achieve the above object, the present invention provides a name identification and association recommendation method, including:
acquiring an accessory name;
identifying an associated name of the accessory name, wherein the associated name is a school name having a name association relationship with the accessory name, and the name association relationship is a case that the school name and a colloquial name thereof have a consistent word with the accessory name;
summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names;
acquiring at least one accessory information from a transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information;
setting the accessory information selected by the user side as target information, acquiring accessory information having an accessory incidence relation with the target information, summarizing to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information;
and when the user side sends a confirmation signal, summarizing the transaction information to form order information, and sending the order information to the transaction system for accessory transaction.
In the above scheme, before the obtaining the accessory name, the method further includes:
constructing a library cluster consisting of at least one sub-database, and establishing a tagged vocabulary set consisting of at least one tagged vocabulary in the sub-database; the sub-database is provided with file tables for recording the school names and the common names of the vehicle accessories, the marked vocabularies are keywords of the school names and the common names in the file tables in the sub-database, and a base table association relation is constructed between the marked vocabularies and the file tables with the marked vocabularies.
In the above scheme, before the obtaining the accessory name, the method further includes:
receiving a selection request sent by a user side, sending a selection module with vehicle type options to the user side according to the selection request, and receiving vehicle type information generated by the user side operating the vehicle type options.
In the above scheme, before the obtaining the accessory name, the method further includes:
the method comprises the steps of receiving a shooting request sent by a user side, calling a shooting module of the user side according to the shooting request to shoot a frame number of a vehicle to obtain a data image, calling a preset OCR component to analyze frame number information in the data image, and analyzing the frame number information to obtain vehicle type information of the vehicle.
In the above scheme, before the obtaining the accessory name, the method further includes:
and receiving the frame number information sent by the user side, and analyzing the frame number information to obtain the vehicle type information of the vehicle.
In the above solution, the step of identifying the associated name of the accessory name includes:
performing word segmentation on the accessory name to obtain at least one accessory vocabulary;
acquiring a marked vocabulary set from a sub-database of the library cluster, comparing the accessory vocabulary with the marked vocabulary in the marked vocabulary set one by one, setting the marked vocabulary consistent with the accessory vocabulary as a target vocabulary, setting the marked vocabulary set with the target vocabulary as the target vocabulary set, and setting the sub-database corresponding to the target vocabulary set as a target database;
identifying a file table in the target database, wherein the file table has a base table association relationship with the target vocabulary, and extracting the school name recorded in the file table as the association name so as to realize the technical effect of identifying the school name having a name association relationship with the accessory name, wherein the base table association relationship refers to the condition that the marked vocabulary appears in the school name or the common name recorded in the file table;
after sending the order information to the trading system for accessory trading, the method further comprises:
and uploading the order information to a block chain.
In the foregoing solution, after receiving the association name selected by the user side in the association list and setting the association name as the target name, the method further includes:
and acquiring at least one accessory information from the transaction system according to the target name and the vehicle type information, summarizing to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
In order to achieve the above object, the present invention further provides a name recognition and association recommendation apparatus, connected to a transaction system, including:
the name input module is used for acquiring the names of the accessories;
the association identification module is used for identifying an association name of the accessory name, wherein the association name is a school name having a name association relationship with the accessory name, and the name association relationship is a condition that the school name and a colloquial name thereof have consistent words with the accessory name;
the target selection module is used for summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names;
the transaction identification module is used for acquiring at least one accessory information from the transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list and setting the accessory information as transaction information;
the transaction recommendation module is used for setting the accessory information selected by the user side as target information, acquiring accessory information having accessory incidence relation with the target information and summarizing the accessory information to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information;
and the order management module is used for summarizing the transaction information to form order information when monitoring that the user side sends a confirmation signal, and sending the order information to the transaction system for accessory transaction.
In order to achieve the above object, the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor of the computer device executes the computer program to implement the steps of the name identification and association recommendation method.
In order to achieve the above object, the present invention further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the steps of the name identification and association recommendation method.
According to the name identification and association recommendation method, device, computer equipment and storage medium, the association name of the accessory name is identified and summarized to obtain the association list, the academic name of the accessory name is obtained in a mode that the association name selected by the user side in the association list is set as the target name, and the accessory required by the user side is accurately identified; acquiring accessory information from the transaction system through the target name, summarizing the accessory information to form an accessory list, and selecting transaction information on the accessory list by the user side, so that the problem that the transaction efficiency and accuracy are low due to frequent communication with accessory suppliers in the current transaction operation of vehicle accessories is solved; at the same time, the user can select the desired position,
the accessory information which is selected by the user side is set as the target information, the accessory information which has the accessory incidence relation with the target information is obtained and summarized to form the recommendation list, and the accessory information which is possibly needed by the user side is sent to the user side, so that the accessory transaction efficiency is further improved.
Drawings
FIG. 1 is a flowchart of a first embodiment of a name identification and association recommendation method of the present invention;
FIG. 2 is a schematic diagram of an environment application of a name identification and association recommendation method according to a second embodiment of the name identification and association recommendation method of the present invention;
FIG. 3 is a flowchart of a name identification and association recommendation method according to a second embodiment of the present invention;
FIG. 4 is a schematic diagram of program modules of a third embodiment of the name identification and association recommendation device of the present invention;
fig. 5 is a schematic diagram of a hardware structure of a computer device according to a fourth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a name identification and association recommendation method, a name identification and association recommendation device, computer equipment and a storage medium, which are suitable for the technical field of data analysis of big data and are used for providing a name identification and association recommendation method based on a name input module, an association identification module, a target selection module, a transaction identification module, a transaction recommendation module and an order management module. Acquiring an accessory name, identifying an association name of the accessory name, summarizing the association name to obtain an association list, acquiring the association name selected by a user side in the association list, and setting the association name as a target name; acquiring at least one accessory information from the transaction system according to the target name, summarizing to form an accessory list, acquiring accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information; setting the accessory information selected by the user side as target information, acquiring accessory information having accessory incidence relation with the target information, summarizing to form a recommendation list, and acquiring the accessory information selected by the user side in the recommendation list as transaction information; and summarizing the transaction information to form order information, and sending the order information to a transaction system for accessory transaction.
The first embodiment is as follows:
referring to fig. 1, a name identification and association recommendation method of the present embodiment, which is executed in a transaction system, includes:
s104: the accessory name is obtained.
S105: and identifying an associated name of the accessory name, wherein the associated name is an academic name having a name associated relationship with the accessory name, and the name associated relationship is a condition that the academic name and a colloquial name thereof have a consistent word with the accessory name.
S106: and summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names.
S107: and acquiring at least one accessory information from the transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
S109: and setting the accessory information selected by the user side as target information, acquiring the accessory information having accessory association relation with the target information, summarizing to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information.
S110: and when the user side sends a confirmation signal, summarizing the transaction information to form order information, and sending the order information to the transaction system for accessory transaction.
In an exemplary embodiment, a name input box is sent to a user terminal according to the vehicle type information, and an accessory name entered in the name input box by the user terminal is received, wherein the name data box can be arranged in a network page or arranged in a popup box.
By identifying the association name of the accessory name, the academic name having the association relation with the accessory name is obtained, so that the accessory information is searched through the academic name, the shop or the commodity selling window of the corresponding seller can be searched with highest accuracy, the accessory information required by the user terminal (such as the shop or the commodity selling window of the accessory seller in the transaction system) can be accurately searched according to the accessory name, and the situation that the accessory transaction process is complicated and inefficient due to frequent communication between the user terminal and the transaction system is avoided.
By the method of feeding back the association list to the user side and selecting the target name from the association list by the user side, the accuracy of accessory information search is powerfully guaranteed. Searching in the transaction system by using the target name as a keyword to obtain at least one accessory information and summarize the accessory information to form an accessory list, sending the accessory list to a user side for selection by the user, and taking the accessory information selected by the user in the accessory list as transaction information and loading the transaction information into a preset shopping cart; because the user may need to purchase various commodities, the transaction information selected by the user is stored in the shopping cart, so that the user can conveniently and quickly select the commodities for multiple times, and the final one-time settlement is carried out, thereby improving the transaction efficiency of the user.
The accessory information selected by the user side is set as target information, a preset clustering model is called to obtain accessory information with accessory incidence relation with the target information, the accessory information is collected to form a recommendation list, the recommendation list is sent to the user side, so that the user side can select the accessory information and set the accessory information as transaction information, and the transaction information is stored in a preset shopping cart (namely a cache module for storing the transaction information), wherein the accessory incidence relation is historical transaction information with the accessory information overlapped with the target information, the convenience of obtaining the relevant accessory information by the user side is improved, and the problem that the transaction efficiency is low due to frequent inquiry of the accessory information required by the user side is solved.
When a confirmation signal generated by operating a confirmation key or a settlement key at a user side is monitored, transaction information in the shopping cart is extracted and summarized to form order information, and the order information is sent to the transaction system to complete the transaction of accessories.
In conclusion, the accessory required by the user side is accurately identified by acquiring the academic name of the accessory name, so that the problem that the transaction efficiency and accuracy are low due to frequent communication with accessory suppliers in the current transaction operation of the vehicle accessory is solved; meanwhile, the accessory transaction efficiency is further improved by sending accessory information which may be needed by the user side to the user side.
Example two:
the embodiment is a specific application scenario of the first embodiment, and the method provided by the present invention can be more clearly and specifically explained through the embodiment.
The method provided by the present embodiment will be specifically described below by taking an example of acquiring the academic name of the accessory name and identifying the transaction information required by the user side in the server running the name identification and association recommendation method. It should be noted that the present embodiment is only exemplary, and does not limit the protection scope of the embodiments of the present invention.
Fig. 2 schematically shows an environment application diagram of a name identification and association recommendation method according to the second embodiment of the present application.
In an exemplary embodiment, the server 2 where the name identification and associated recommendation method is located is connected with the transaction system 3 and the user terminal 4 through a network; the server 2 may provide services through one or more networks, which may include various network devices, such as routers, switches, multiplexers, hubs, modems, bridges, repeaters, firewalls, proxy devices, and/or the like. The network may include physical links, such as coaxial cable links, twisted pair cable links, fiber optic links, combinations thereof, and/or the like. The network may include wireless links, such as cellular links, satellite links, Wi-Fi links, and/or the like; the user terminal 4 may be a computer device such as a smart phone, a tablet computer, a notebook computer, and a desktop computer.
Fig. 3 is a flowchart of a specific method of name recognition and association recommendation according to an embodiment of the present invention, and the method specifically includes steps S200 to S210.
S200: constructing a library cluster consisting of at least one sub-database, and establishing a tagged vocabulary set consisting of at least one tagged vocabulary in the sub-database; the sub-database is provided with file tables for recording the school names and the common names of the vehicle accessories, the marked vocabularies are keywords of the school names and the common names in the file tables in the sub-database, and a base table association relation is constructed between the marked vocabularies and the file tables with the marked vocabularies.
The accessory name input by the user is usually a local common name, and the problems of inaccurate matching, wrong search results and the like are often caused by directly using the common name to search the accessory required by the user, so that the learning name of each automobile accessory can be quickly and accurately obtained to ensure the accuracy of accessory searching; the method comprises the steps of building a library cluster which is composed of at least one sub-database, building a tagged word collection which is composed of at least one tagged word in the sub-database, wherein the sub-database is provided with a file list which records the academic name and the popular name of the vehicle accessory, the tagged word is a keyword of the academic name and the popular name in each file list in the sub-database, and building a library table incidence relation between the tagged word and the file list in which the tagged word appears. Comparing the obtained accessory name with a standard vocabulary to identify the standard vocabulary appearing in the accessory name and set the standard vocabulary as a target vocabulary, identifying a file list associated with the target vocabulary and extracting the academic name of the file list to obtain the academic name corresponding to the obtained accessory name (usually a common name).
In a preferred embodiment, the step of constructing a library cluster composed of at least one sub-database, and establishing a tagged vocabulary set composed of at least one tagged vocabulary in the sub-database includes:
s01: constructing a library cluster consisting of at least one sub-database, and setting a category label of the sub-database, wherein the category label reflects the category of the accessory.
In this step, the categories are general descriptions of components of the vehicle, such as: an engine section, a chassis section, a body section, an electrical section, and the like; setting a category label of the sub-database to define the category of the academic name and the colloquial name stored in the sub-database.
S02: and acquiring the academic name and the popular name of the accessory belonging to the category mark from a preset accessory library, sending the academic name and the popular name to a sub-database with the category mark, and constructing a file list for storing the academic name and the popular name in the sub-database.
In this step, the academic name and the popular name of any accessory under a certain category mark are obtained from the accessory library, a file list used for storing the academic name and the popular name is constructed in a sub-database, and the academic name and the popular name are stored in the file list, wherein the accessory library is a database storing the academic name and the popular name corresponding to the accessory of each vehicle.
S03: and segmenting the academic name and the popular name in the file list, removing the duplication to obtain a marked vocabulary, and associating the marked vocabulary with the file list.
In the step, the academic name and the popular name are segmented through a Chinese segmentation component (such as word segmentation), the marked vocabulary is used as a main key through a key-value method, and the file table is used as a key value to realize the effect of associating the marked vocabulary with the file table.
S04: and summarizing the marked vocabularies of all the file tables in the sub-database, removing the duplication to obtain a marked word set, and associating the marked word set with the sub-database.
In this step, the tagged vocabulary is set in the configuration file of the sub-database, so that the tagged vocabulary is called conveniently, and the technical effect of associating the tagged vocabulary with the sub-database is achieved.
S201: receiving a selection request sent by a user side, sending a selection module with vehicle type options to the user side according to the selection request, and receiving vehicle type information generated by the user side operating the vehicle type options.
In order to acquire a vehicle type corresponding to an accessory required by a user to ensure the accuracy of subsequent accessory information acquisition, a selection module is sent to a user side according to a selection request sent by the user side, specifically, a home page with a selection key is sent to the user side, a selection request is generated by a receiving user side by clicking the selection key, the selection module is extracted from a preset module library according to the selection request, and the selection module is a page or a bullet frame with vehicle type options; and the vehicle type options comprise brands, annual payments and sales styles. Further, a vehicle type option operated on the option module (i.e. page or pop-up box) by the user side is received, which comprises: brand, annual account, sales style, and obtain selection information, such as: the BMW 2019, 320i M sports suit.
S202: the method comprises the steps of receiving a shooting request sent by a user side, calling a shooting module of the user side according to the shooting request to shoot a frame number of a vehicle to obtain a data image, calling a preset OCR component to analyze frame number information in the data image, and analyzing the frame number information to obtain vehicle type information of the vehicle.
In order to obtain a vehicle type corresponding to an accessory required by a user and ensure the accuracy of subsequent accessory information acquisition, a shooting module of a user side is called according to a shooting request sent by the user side in the step for shooting a frame number of the vehicle to obtain a data image, specifically, a home page with a shooting key is sent to the user side, the shooting request generated by clicking the shooting key by the user side is received, the shooting page of the user side is called according to the shooting request to enable the user side to enter the shooting page, and the data image generated by shooting the frame number of the vehicle through the shooting page by the user side is received.
Further, calling a preset OCR component to identify a frame number image in the data image, wherein the frame number image is data information for displaying a frame number in the data image in an image form;
analyzing the frame number image through the OCR component to obtain frame number information, wherein the frame number information is data information which shows the frame number in an editable data form, so that a server can analyze and calculate the frame number of the vehicle;
and analyzing the frame number information through a preset frame number analyzing component to obtain the vehicle type information.
In this embodiment, the OCR component (Optical Character Recognition) refers to a computer component that an electronic device (e.g., a scanner or a digital camera) examines a Character printed on a paper, determines its shape by detecting dark and light patterns, and then translates the shape into a computer text by a Character Recognition method.
The Vehicle frame Number is also called Vehicle Identification Number VIN, and the English name is called Vehicle Identification Number. Is a set of code words assigned to vehicles by manufacturers for identification according to preset frame number rules.
The frame number analysis component is a computer component for analyzing the frame number information according to the frame number rule to obtain the brand, the annual amount and the sale style of the vehicle.
S203: and receiving the frame number information sent by the user side, and analyzing the frame number information to obtain the vehicle type information of the vehicle.
In order to obtain the vehicle type corresponding to the accessory required by the user and ensure the accuracy of subsequently obtaining accessory information, the step obtains vehicle type information from a preset vehicle type library according to the received vehicle frame number information; specifically, a home page with a frame number input frame is sent to a user side, and frame number information input by the user side in the frame number input frame is received, wherein the frame number information is data information for displaying the frame number in an editable data form, so that a server can analyze and calculate the frame number of the vehicle; and analyzing the frame number information through a preset frame number analyzing component to obtain the vehicle type information.
S204: the accessory name is obtained.
Specifically, a name input box is sent to a user side according to the vehicle type information, and an accessory name input by the user side in the name input box is received, wherein the name data box can be arranged in a network page or arranged in a pop-up box.
S205: and identifying an associated name of the accessory name, wherein the associated name is an academic name having a name associated relationship with the accessory name, and the name associated relationship is a condition that the academic name and a colloquial name thereof have a consistent word with the accessory name.
In order to ensure that accessory information required by a user terminal (such as a shop or a commodity selling window of an accessory seller in a transaction system) can be accurately searched according to accessory names and avoid the situation that the accessory transaction process is complicated and inefficient due to frequent communication between the user terminal and the transaction system, the step identifies the associated names of the accessory names to obtain the scholars with the associated relations with the accessory names, so that the accessory information is searched through the scholars, and the shop or the commodity selling window of the corresponding seller can be searched with highest accuracy.
In a preferred embodiment, the step of identifying the associated name of the accessory name comprises:
s51: and performing word segmentation on the accessory name to obtain at least one accessory vocabulary.
S52: and acquiring a marked vocabulary set from a sub-database of the library cluster, comparing the accessory vocabulary with the marked vocabulary in the marked vocabulary set one by one, setting the marked vocabulary consistent with the accessory vocabulary as a target vocabulary, setting the marked vocabulary set with the target vocabulary as the target vocabulary set, and setting the sub-database corresponding to the target vocabulary set as a target database.
S53: and identifying a file table in the target database, wherein the file table has a table association relation with the target vocabulary, and extracting the school name recorded in the file table as the association name so as to realize the technical effect of identifying the school name having a name association relation with the accessory name, wherein the table association relation refers to the situation that the marked vocabulary appears in the school name or the common name recorded in the file table.
S206: and summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names.
Since there may be a plurality of association names having name association relation with the accessory names, the accuracy of searching for accessory information is strongly ensured by feeding back the association list to the user side and selecting the target name in the association list by the user side.
In a preferred embodiment, the step of summarizing the association names to obtain an association list includes:
s61: and calculating the number of words with the name association relationship between the association name and the colloquial name thereof and the accessory name.
S62: and performing descending order on the association names according to the number to obtain an association list.
In order to facilitate the user side to quickly select the academic name with the highest degree of association with the accessory name, the step obtains an association list with at least one association name by sequencing the association names according to the number of the target vocabularies corresponding to the association names, and if the number of words with name association relationship between the association name a and the colloquial name thereof and the accessory name is 2 and the number of association names B is 1, the association name a is arranged at the first position and the association name B is arranged at the second position in the association list.
S207: and acquiring at least one accessory information from the transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
In this step, the target name is a keyword which is searched in the transaction system to obtain at least one accessory information and collect the accessory information to form an accessory list, the accessory list is sent to a user side for selection by a user, and the accessory information selected by the user in the accessory list is used as transaction information and loaded into a preset shopping cart; because the user may need to purchase various commodities, the transaction information selected by the user is stored in the shopping cart, so that the user can conveniently and quickly select the commodities for multiple times, and the final one-time settlement is carried out, thereby improving the transaction efficiency of the user.
It should be noted that the transaction system refers to an internet shopping platform (e.g., naobao, kyoto, many spellings, creation, etc.), and in this step, the target name is used as a search keyword to perform accessory information on the transaction system, such as: the merchant stores, the merchandise sales windows, etc. are searched, and therefore, the technical principle of the transaction system is not described in detail in the present application.
S208: and acquiring at least one accessory information from the transaction system according to the target name and the vehicle type information, summarizing to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
In the step, the target name and the vehicle type information are used as keywords to search in the transaction system, at least one accessory information is obtained and summarized to form an accessory list, so that the accuracy of the accessory information in the accessory list is improved, and the information query requirement of a user is further accurately met; sending the accessory list to a user side for selection of a user, taking the accessory information selected by the user in the accessory list as transaction information and loading the transaction information into a preset shopping cart (namely a cache module for storing the transaction information); because the user may need to purchase various commodities, the transaction information selected by the user is stored in the shopping cart, so that the user can conveniently and quickly select the commodities for multiple times, and the final one-time settlement is carried out, thereby improving the transaction efficiency of the user.
S209: and setting the accessory information selected by the user side as target information, acquiring the accessory information having accessory association relation with the target information, summarizing to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information.
In order to improve the convenience of acquiring related accessory information by a user side and avoid the problem that the transaction efficiency is low due to frequent inquiry of accessory information required by the user side, the accessory information selected by the user side is set as target information, a preset clustering model is called to acquire the accessory information having accessory association relation with the target information, the accessory information is collected to form a recommendation list, the recommendation list is sent to the user side so that the user side can select the accessory information and set the accessory information as transaction information, and the transaction information is stored in a preset shopping cart (namely a cache module for storing the transaction information), wherein the accessory association relation is historical transaction information having the accessory information which is overlapped with the target information.
In this embodiment, the clustering model is obtained by the following steps:
m1: acquiring historical transaction information, and vectorizing the historical transaction information to obtain historical transaction data; the historical transaction information comprises at least one accessory information of any user end and the transaction system for completing transaction in history.
In this step, one-hot codes are adopted to conduct vectorization processing on the historical transaction information, wherein the accessory information corresponding to the transaction information has unique codes.
Illustratively, the historical transaction information is such as:
the user side A purchases accessory information A, accessory information B and accessory information C;
the user side B purchases the accessory information B and the accessory information D;
the user side C purchases the accessory information D and the accessory information E.
Assume that the code of the accessory information a is (1,0,0,0,0), the code of the accessory information B is (0,1,0,0,0), the code of the accessory information C is (0,0,1,0,0), the code of the accessory information D is (0,0,0,1,0), and the code of the accessory information E is (0,0,0,0, 1).
The resulting transaction data is then as follows:
(1,1,1,0,0)(0,1,0,1,0)(0,0,0,1,1)。
m2: and recording the historical transaction data into a preset scatter model to be used as a historical scatter.
In this step, matlab is used to construct a scattered point model capable of converting vectorized data into scattered points, and since the historical transaction information is usually unordered and has no definite target, if a k-mean clustering algorithm is used to forcedly classify the historical transaction data, several clusters specified by strong association relationship are present, which easily causes fitting information in a recommendation list to be over-fitted, that is: and forcibly recommending the transaction information generated by other user sides to the user side according to the historical transaction information, and finally causing the contents of the recommended list to be inaccurate. And because the historical transaction information is truly generated, the transaction data which is truly generated by the history can be recommended to the user side, and the recommendation list can be sent to the user side more closely and realistically, so that the historical scatter associated with the target scatter corresponding to the target data is obtained subsequently through the scatter model, the recommendation accuracy of the accessory information is improved, and the operation rate of the recommended accessory information is increased.
In a preferred embodiment, the step of obtaining the accessory information having an accessory association relationship with the target information and summarizing to form a recommendation list includes:
s91: and vectorizing the target information to obtain target data.
In this step, one-hot codes are adopted to carry out vectorization processing on the target information, wherein the accessory information corresponding to the target information has unique codes.
Illustratively, the target information is as follows:
the user terminal D purchases the accessory information E.
The target data obtained is then as follows:
(0,0,0,0,1)。
s92: and inputting the target data into the scattered point model to obtain a target scattered point, calling a preset distance threshold value in the scattered point model, and defining a target range in the scattered point model by taking the target scattered point as a circle center and the distance threshold value as a radius.
In this step, a distance calculation method (e.g., calculating the Euclidean distance between scattered points) by means of a mean shift clustering algorithm defines a target range in a scattered point model by taking a target scattered point as a circle center and a distance threshold as a radius, that is, the Euclidean distance from the target scattered point is less than or equal to the range of the distance threshold.
S93: and acquiring historical scatter points in the target range and historical transaction information corresponding to the historical scatter points, wherein the historical transaction information comprises accessory information of any historical user end completing transaction with the transaction system, and the historical scatter points are vectorized embodiment of the historical transaction information in a scatter point model.
Illustratively, based on the above example, assuming that the distance threshold is 1.6, the distance between the target scatter and the historical scatter is calculated, and (0,1,0,1,0) (0,0,0,1,1) is obtained as the historical scatter belonging to the target delineation range.
S94: and summarizing the historical transaction information, removing the duplication to obtain a to-be-recommended list with at least one piece of historical transaction information, and deleting the target information in the to-be-recommended list to obtain a recommended list.
Illustratively, based on the above example, the obtained list to be recommended includes:
accessory information B, accessory information D, and accessory information E.
The recommendation list obtained by deleting the target information in the list to be recommended comprises the following steps:
accessory information B and accessory information D.
S210: and when the user side sends a confirmation signal, summarizing the transaction information to form order information, and sending the order information to the transaction system for accessory transaction.
In the step, when a confirmation signal generated by operating a confirmation key or a settlement key at a user side is monitored, transaction information in the shopping cart is extracted and summarized to form order information, and the order information is sent to the transaction system to complete the transaction of accessories.
After sending the order information to the trading system for accessory trading, the method further comprises:
and uploading the order information to a block chain.
It should be noted that the corresponding summary information is obtained based on the order information, and specifically, the summary information is obtained by hashing the order information, for example, by using the sha256s algorithm. Uploading summary information to the blockchain can ensure the safety and the fair transparency of the user. The user equipment can download the summary information from the blockchain so as to verify whether the order information is tampered. The blockchain referred to in this example is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm, and the like. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
Example three:
referring to fig. 4, a name recognition and association recommending apparatus 1 of the present embodiment includes:
a name input module 14, configured to obtain an accessory name;
the association identification module 15 is configured to identify an association name of the accessory name, where the association name is a school name having a name association relationship with the accessory name, and the name association relationship is a case where the school name and a colloquial name thereof have a consistent word with the accessory name;
the target selection module 16 is configured to summarize the association names to obtain an association list, send the association list to the user side, receive the association names selected by the user side in the association list, and set the association names as target names;
the transaction identification module 17 is configured to obtain at least one accessory information from the transaction system according to the target name, collect the accessory information to form an accessory list, send the accessory list to the user side, receive the accessory information selected by the user side on the accessory list, and set the accessory information as transaction information;
the transaction recommendation module 19 is configured to set the accessory information selected by the user side as target information, acquire accessory information having an accessory association relationship with the target information, summarize the accessory information to form a recommendation list, send the recommendation list to the user side, and set the accessory information selected by the user side in the recommendation list as transaction information;
and the order management module 20 is configured to, when it is monitored that the user side sends a confirmation signal, summarize the transaction information to form order information, and send the order information to the transaction system for accessory transaction.
Optionally, the name identification and association recommendation apparatus 1 further includes:
the database module 10 is used for constructing a library cluster which is composed of at least one sub-database, and establishing a marked vocabulary set which is composed of at least one marked vocabulary in the sub-database; the sub-database is provided with file tables for recording the school names and the common names of the vehicle accessories, the marked vocabularies are keywords of the school names and the common names in the file tables in the sub-database, and a base table association relation is constructed between the marked vocabularies and the file tables with the marked vocabularies.
Optionally, the name identification and association recommendation apparatus 1 further includes:
the vehicle type selection module 11 is configured to receive a selection request sent by a user, send a selection module with vehicle type options to the user according to the selection request, and receive vehicle type information generated by the user operating the vehicle type options.
Optionally, the name identification and association recommendation apparatus 1 further includes:
the vehicle type shooting module 12 is used for receiving a shooting request sent by a user terminal, calling the shooting module of the user terminal according to the shooting request, shooting the frame number of the vehicle to obtain a data image, calling a preset OCR component to analyze the frame number information in the data image, and analyzing the frame number information to obtain the vehicle type information of the vehicle.
Optionally, the name identification and association recommendation apparatus 1 further includes:
and the vehicle type input module 13 is used for receiving the frame number information sent by the user side and analyzing the frame number information to obtain the vehicle type information of the vehicle.
Optionally, the name identification and association recommendation apparatus 1 further includes:
and the fine identification module 18 is used for acquiring at least one accessory information from the transaction system according to the target name and the vehicle type information, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
Optionally, the database module 10 includes:
the cluster building unit 101 is configured to build a library cluster composed of at least one sub-database, and set a category flag of the sub-database, where the category flag reflects a category to which the accessory belongs.
A name obtaining unit 102, configured to obtain a school name and a colloquial name of an accessory belonging to the category label from a preset accessory library, send the school name and the colloquial name to a sub-database with the category label, and construct a file table in the sub-database for storing the school name and the colloquial name.
And the word segmentation association unit 103 is configured to segment words of the academic name and the popular name in the file list, remove duplication to obtain a tagged word, and associate the tagged word with the file list.
And the set association unit 104 is configured to summarize tagged words of all file tables in the sub-database, remove duplicates to obtain a tagged word set, and associate the tagged word set with the sub-database.
Optionally, the association identification module 15 includes:
and an accessory word segmentation unit 151, configured to perform word segmentation on the accessory name to obtain at least one accessory word.
The target recognition unit 152 is configured to obtain a tagged vocabulary set from the sub-databases of the library cluster, compare the accessory vocabularies with the tagged vocabularies in the tagged vocabulary set one by one, set tagged vocabularies consistent with the accessory vocabularies as target vocabularies, set tagged vocabulary sets with the target vocabularies as target vocabulary sets, and set the sub-databases corresponding to the target vocabulary sets as target databases.
The file table identifying unit 153 is configured to identify a file table in the target database, where the file table has a table association relationship with the target vocabulary, and extract the school name recorded in the file table as the association name, so as to achieve a technical effect of identifying the school name having a name association relationship with the accessory name, where the table association relationship is a situation where a tagged vocabulary appears in the school name or a colloquial name recorded in the file table.
Optionally, the target selecting module 16 includes:
the calculating unit 161 is configured to calculate the number of words having the name association relationship between the association name and the colloquial name thereof and the accessory name.
And the arranging unit 162 is configured to perform descending order arrangement on the association names according to the number to obtain an association list.
Optionally, the transaction recommendation module 19 includes:
and the vectorization unit 191 is configured to perform vectorization processing on the target information to obtain target data.
The target delineating unit 192 is configured to record the target data into the scatter model to obtain a target scatter, call a distance threshold preset in the scatter model, and delineate a target range in the scatter model by using the target scatter as a circle center and the distance threshold as a radius.
The association identification unit 193 is configured to obtain historical scatter in the target range, and obtain historical transaction information corresponding to the historical scatter, where the historical transaction information includes accessory information of any historical user end that completes a transaction with the transaction system, and the historical scatter is a vectorization representation of the historical transaction information in a scatter model.
And the list constructing unit 194 is configured to collect the historical transaction information, obtain a to-be-recommended list with at least one piece of historical transaction information by deduplication, and obtain a recommended list by deleting the target information in the to-be-recommended list.
The technical scheme is applied to the field of data analysis of big data, accessory information with an accessory incidence relation with the target information is obtained and summarized to form a recommendation list by setting the accessory information selected by the user side as the target information, and the technical effect of intelligently recommending the accessory information to the user side is achieved by analyzing the relation between the target information and other accessory information through a network.
Example four:
in order to achieve the above object, the present invention further provides a computer device 5, where components of the name recognition and association recommendation apparatus in the third embodiment may be distributed in different computer devices, and the computer device 5 may be a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server, or a rack server (including an independent server or a server cluster formed by multiple application servers) that executes a program. The computer device of the embodiment at least includes but is not limited to: a memory 51, a processor 52, which may be communicatively coupled to each other via a system bus, as shown in FIG. 5. It should be noted that fig. 5 only shows a computer device with components, but it should be understood that not all of the shown components are required to be implemented, and more or fewer components may be implemented instead.
In this embodiment, the memory 51 (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the memory 51 may be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the memory 51 may be an external storage device of a computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computer device. Of course, the memory 51 may also include both internal and external storage devices of the computer device. In this embodiment, the memory 51 is generally used for storing an operating system and various application software installed on the computer device, such as the program code of the name identification and association recommendation apparatus in the third embodiment. Further, the memory 51 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 52 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 52 is typically used to control the overall operation of the computer device. In this embodiment, the processor 52 is configured to run the program codes stored in the memory 51 or process data, such as running the name recognition and association recommendation apparatus, so as to implement the name recognition and association recommendation method of the first embodiment and the second embodiment.
Example five:
to achieve the above objects, the present invention also provides a computer readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., on which a computer program is stored, which when executed by a processor 52, implements corresponding functions. The computer-readable storage medium of the present embodiment is used for storing a name identification and association recommendation apparatus, and when executed by the processor 52, implements the name identification and association recommendation method of the first embodiment and the second embodiment.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. A name identification and association recommendation method is characterized by comprising the following steps:
acquiring an accessory name;
identifying an associated name of the accessory name, wherein the associated name is a school name having a name association relationship with the accessory name, and the name association relationship is a case that the school name and a colloquial name thereof have a consistent word with the accessory name;
summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names;
acquiring at least one accessory information from a transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information;
setting the accessory information selected by the user side as target information, acquiring accessory information having an accessory incidence relation with the target information, summarizing to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information;
and when the user side sends a confirmation signal, summarizing the transaction information to form order information, and sending the order information to the transaction system for accessory transaction.
2. The name recognition and association recommendation method of claim 1, wherein prior to said obtaining an accessory name, said method further comprises:
constructing a library cluster consisting of at least one sub-database, and establishing a tagged vocabulary set consisting of at least one tagged vocabulary in the sub-database; the sub-database is provided with file tables for recording the school names and the common names of the vehicle accessories, the marked vocabularies are keywords of the school names and the common names in the file tables in the sub-database, and a base table association relation is constructed between the marked vocabularies and the file tables with the marked vocabularies.
3. The name recognition and association recommendation method of claim 1, wherein prior to said obtaining an accessory name, said method further comprises:
receiving a selection request sent by a user side, sending a selection module with vehicle type options to the user side according to the selection request, and receiving vehicle type information generated by the user side operating the vehicle type options.
4. The name recognition and association recommendation method of claim 1, wherein prior to said obtaining an accessory name, said method further comprises:
the method comprises the steps of receiving a shooting request sent by a user side, calling a shooting module of the user side according to the shooting request to shoot a frame number of a vehicle to obtain a data image, calling a preset OCR component to analyze frame number information in the data image, and analyzing the frame number information to obtain vehicle type information of the vehicle.
5. The name recognition and association recommendation method of claim 1, wherein prior to said obtaining an accessory name, said method further comprises:
and receiving the frame number information sent by the user side, and analyzing the frame number information to obtain the vehicle type information of the vehicle.
6. The name recognition and association recommendation method of claim 2, wherein the step of recognizing the associated name of the accessory name comprises:
performing word segmentation on the accessory name to obtain at least one accessory vocabulary;
acquiring a marked vocabulary set from a sub-database of the library cluster, comparing the accessory vocabulary with the marked vocabulary in the marked vocabulary set one by one, setting the marked vocabulary consistent with the accessory vocabulary as a target vocabulary, setting the marked vocabulary set with the target vocabulary as the target vocabulary set, and setting the sub-database corresponding to the target vocabulary set as a target database;
identifying a file table in the target database, wherein the file table has a base table association relationship with the target vocabulary, and extracting the school name recorded in the file table as the association name so as to realize the technical effect of identifying the school name having a name association relationship with the accessory name, wherein the base table association relationship refers to the condition that the marked vocabulary appears in the school name or the common name recorded in the file table;
after sending the order information to the trading system for accessory trading, the method further comprises:
and uploading the order information to a block chain.
7. The method for name recognition and association recommendation according to any of claims 3-5, wherein after receiving the association name selected by the user end in the association list and setting it as the target name, the method further comprises:
and acquiring at least one accessory information from the transaction system according to the target name and the vehicle type information, summarizing to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list, and setting the accessory information as transaction information.
8. A name identification and association recommendation device connected with a transaction system is characterized by comprising:
the name input module is used for acquiring the names of the accessories;
the association identification module is used for identifying an association name of the accessory name, wherein the association name is a school name having a name association relationship with the accessory name, and the name association relationship is a condition that the school name and a colloquial name thereof have consistent words with the accessory name;
the target selection module is used for summarizing the association names to obtain an association list, sending the association list to the user side, receiving the association names selected by the user side in the association list and setting the association names as target names;
the transaction identification module is used for acquiring at least one accessory information from the transaction system according to the target name, summarizing the accessory information to form an accessory list, sending the accessory list to the user side, receiving the accessory information selected by the user side on the accessory list and setting the accessory information as transaction information;
the transaction recommendation module is used for setting the accessory information selected by the user side as target information, acquiring accessory information having accessory incidence relation with the target information and summarizing the accessory information to form a recommendation list, sending the recommendation list to the user side, and setting the accessory information selected by the user side in the recommendation list as transaction information;
and the order management module is used for summarizing the transaction information to form order information when monitoring that the user side sends a confirmation signal, and sending the order information to the transaction system for accessory transaction.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the name identification and association recommendation method of any one of claims 1 to 7 are implemented when the computer program is executed by the processor of the computer device.
10. A computer-readable storage medium, on which a computer program is stored, the computer program stored in the computer-readable storage medium, when being executed by a processor, implementing the steps of the name identification and association recommendation method according to any one of claims 1 to 7.
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