CN113849695B - Method and system for intelligently searching vehicle types based on vehicle groups - Google Patents
Method and system for intelligently searching vehicle types based on vehicle groups Download PDFInfo
- Publication number
- CN113849695B CN113849695B CN202110524992.8A CN202110524992A CN113849695B CN 113849695 B CN113849695 B CN 113849695B CN 202110524992 A CN202110524992 A CN 202110524992A CN 113849695 B CN113849695 B CN 113849695B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- catalog
- brand
- selection
- user
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 18
- 238000006073 displacement reaction Methods 0.000 claims abstract description 56
- 238000004519 manufacturing process Methods 0.000 claims abstract description 31
- 238000012216 screening Methods 0.000 claims description 10
- 230000001174 ascending effect Effects 0.000 claims description 3
- 238000004321 preservation Methods 0.000 claims description 2
- 238000010187 selection method Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9017—Indexing; Data structures therefor; Storage structures using directory or table look-up
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9032—Query formulation
- G06F16/90324—Query formulation using system suggestions
- G06F16/90328—Query formulation using system suggestions using search space presentation or visualization, e.g. category or range presentation and selection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9038—Presentation of query results
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Software Systems (AREA)
- Mathematical Physics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- User Interface Of Digital Computer (AREA)
Abstract
The invention discloses a method and a system for intelligently searching vehicle types based on a vehicle group, which belong to the technical field of information retrieval, and comprise a vehicle type database, a search frame module and a selection frame module, wherein the vehicle type database comprises a plurality of vehicle types, the vehicle types are classified by brands, manufacturers, vehicle systems and displacement, the vehicle systems are classified by the vehicle groups, the vehicle group comprises a vehicle chassis number, a vehicle algebra and a production year, the vehicle types with the same vehicle chassis number and the same vehicle algebra are divided into the same vehicle group and display the minimum production year and the maximum production year of the vehicle group, the selection frame module is used for displaying the catalogue of the vehicle type database for a user to select and screen the vehicle types of the vehicle type database, and the search frame module is used for inputting keywords by the user and matching the keywords to the vehicle type database. The invention simplifies the vehicle type selection method, meets the multi-level operation requirement, and can achieve rapid and accurate selection by inputting a plurality of keywords, thereby reducing the operation time of the user and improving the selection efficiency of the user.
Description
Technical Field
The invention belongs to the technical field of information retrieval, and particularly relates to a method and a system for intelligently retrieving vehicle types based on a vehicle group.
Background
Along with the rapid development of automobile industry in China for more than 20 years, automobile brands produced and sold in China have hundreds, and detailed automobile types reach more than 20 tens of thousands. In the whole life cycle from the sale of the vehicle to the scrapping, all parties such as the assembly manufacturers, the assembly distributors, the maintenance factories, the car owners and the like need a system and a method capable of quickly and conveniently inquiring the vehicle type. The existing vehicle type query system and query mode are mainly selected according to brands, manufacturers, vehicle systems, annual fee and discharge grade. The problems are:
The selection steps are complicated and low in efficiency, only forward progressive selection is supported, the middle level is not supported for starting the selection, and the customer needs to select layer by layer to find the corresponding vehicle type range;
When an unfamiliar vehicle is encountered, multiple stages of repeated selection search are needed;
There is no way to distinguish between hot and cold vehicles.
Disclosure of Invention
Technical problems: aiming at the problems in the prior art, the technical problem to be solved by the invention is to provide a method and a system for intelligently searching vehicle types based on a vehicle group, which simplify the step of searching the vehicle types by a user, meet the requirement that the user operates in multiple layers without searching from the first level of the initial layer of the system, save time and improve efficiency.
The technical scheme is as follows: in order to solve the technical problems, the invention adopts the following technical scheme:
The utility model provides a car model system is retrieved to intelligence based on car group, includes motorcycle type database, search box module and selection box module, motorcycle type database includes a plurality of motorcycle type, a plurality of motorcycle type is categorised through brand, producer, train, discharge capacity, the train is categorised through the car group, the car group includes chassis number, car algebra and year of production, chassis number and car algebra the same motorcycle type divide into same car group and show the minimum year of production and the biggest year of production of this car group, the selection box module is used for showing the catalogue of motorcycle type database supplies the user to select and screens a plurality of motorcycle type database, search box module is used for the user to input the keyword and will the keyword matches to motorcycle type database.
Further, the selection frame module comprises a first selection frame module, a second selection frame module, a third selection frame module and a fourth selection frame module, wherein the first selection frame module is used for displaying the brand catalogue of the brand and selecting by a user, the second selection frame module is used for displaying the manufacturer catalogue of the manufacturer and selecting by the user, the third selection frame module is used for displaying the train catalogue of the train and selecting by the user, and the fourth selection frame module is used for displaying the train catalogue of the train set and selecting by the user.
Further, the manufacturer catalog is a subdirectory of the brand catalog, the train catalog is a subdirectory of the manufacturer catalog, and the consist catalog is a subdirectory of the train catalog.
Further, the selection box module further comprises a fifth selection box module, wherein the fifth selection box module is used for displaying the displacement catalogue of the displacement and selecting the displacement catalogue by a user, and the displacement catalogue is a subdirectory of the catalogue of the vehicle group.
Further, when one of the brand directory, the manufacturer directory, the train directory, the group directory or the displacement directory is displayed, all directories on the upper level and adjacent subdirectories are displayed simultaneously.
Further, the brand catalogue is ordered according to a preset brand pinyin initial rule, and the brand pinyin initial rule is the brand pinyin initial ascending order.
Further, the vehicle model display device further comprises a display frame module, wherein the display frame module is used for displaying a plurality of vehicle models in the vehicle model database after being screened by the selection frame module, and the plurality of vehicle models displayed by the display frame module are ordered according to the vehicle model preservation amount descending order.
The invention also provides a method for intelligently searching the vehicle types based on the vehicle groups, which comprises the following steps:
step 1: acquiring keywords input by a user;
Step 2: the method comprises the steps that a plurality of vehicle types in a vehicle type database are classified level by level according to brands, manufacturers, vehicle systems, vehicle groups and displacement, five levels of brand catalogs, manufacturer catalogs, vehicle system catalogs, vehicle group catalogs and displacement catalogs of the sub-catalogs of the previous level are formed in the next level, keywords in the step 1 are matched with fields of the brands, the manufacturers, the vehicle systems, the vehicle groups and the displacement in the vehicle type database, and the steps are selected level by level:
Step 2.1: when the keyword is a word segment matched with a brand, displaying a brand catalog and a manufacturer catalog, marking the brand related to the keyword, selecting the manufacturer catalog of the next stage for a user, and selecting the manufacturer catalog layer by layer until the displacement catalog is selected;
step 2.2: when the keyword is word segment matched to the manufacturer, displaying brand catalogs, manufacturer catalogs and car catalogs, marking brands and manufacturers related to the keyword, selecting car catalogs of the next stage for users, and selecting the car catalogs layer by layer until the displacement catalogs are selected;
Step 2.3: when the keyword is a word segment matched with the train, displaying a brand catalog, a manufacturer catalog, a train catalog and a train catalog, marking brands, manufacturers and trains related to the keyword, selecting the train catalog of the next stage for a user, and selecting the train catalog layer by layer until the displacement catalog is selected;
Step 2.4: when the keyword is a word segment matched with the train set, displaying a brand directory, a manufacturer directory, a train set directory and a displacement directory, marking brands, manufacturers, train sets and train sets related to the keyword, and selecting the displacement directory of the next stage for a user;
step 2.5: when the keyword is a multi-word segment, splitting the multi-field keyword and then respectively matching, wherein the weight value order of the hit field of the keyword is as follows: the method comprises the steps that a vehicle group > displacement > vehicle system > manufacturer > brand, then one result with the largest weight value in the hit brand, manufacturer, vehicle system, vehicle group or displacement is displayed, the catalog corresponding to the result is displayed, a plurality of superior catalogs and next-level subdirectories of the catalog corresponding to the result are displayed at the same time, the next-level subdirectories are selected by a user, and the next-level subdirectories are selected layer by layer until the displacement catalogs are selected;
Step 3: and (3) displaying screening results in the vehicle model database in a display frame module according to the selection of the client in the step (2), and arranging the screening results in descending order according to the numerical value of the vehicle model holding quantity.
Further, in step 2, the vehicle groups are classified according to the vehicle groups under the same vehicle system under the same brand and the same manufacturer, the vehicle groups comprise data of chassis numbers, algebra and production years, the vehicle types with the same chassis numbers and algebra are classified into the same vehicle group, the minimum production year and the maximum production year of the vehicle group are displayed, and when the keywords are matched with any field of the chassis numbers, the algebra and the production year of the vehicle group, the vehicle group catalogue is directly displayed and the corresponding vehicle group is marked.
Further, in the step 3, only after the user enters the hierarchical selection of the car group directory, the screening result in the car model database is displayed in the display frame module.
The beneficial effects are that: compared with the prior art, the invention has the following advantages: (1) By adding the classification field of the vehicle group, the vehicle type selection method is simplified, and the selection times of users are reduced; (2) The multi-level operation requirement is met, a user familiar with the vehicle type can achieve quick and accurate selection by inputting a plurality of keywords, the operation time of the user is reduced, and the selection efficiency of the user is improved; (3) helping the user to distinguish cold door car models from hot door car models.
Drawings
FIG. 1 is a system interface diagram of an embodiment of the present invention;
FIG. 2 is an exemplary diagram of a consist in an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a method according to an embodiment of the invention.
Detailed Description
The invention will be further illustrated by the following description of specific examples, which are given in connection with the accompanying drawings and are to be construed as illustrative only and not limiting the scope of the invention.
As shown in fig. 1, a vehicle type system based on intelligent vehicle group searching includes a vehicle type database (background operation), a search frame module (i.e. a vehicle type information frame in the figure), a selection frame module (i.e. a plurality of vertical frames below the vehicle type information frame in the figure), wherein the vehicle type database includes a plurality of existing vehicle types, a total quantity of twenty-ten thousands of vehicle types exist in the existing vehicle type database, a code called mid can be defined for each detailed vehicle type, in the prior art, the vehicle types are generally classified by fields such as brands, manufacturers, vehicle systems, displacement, etc., different vehicle types are firstly classified according to vehicle brands, the same brands are classified according to manufacturers, the same manufacturers are classified according to vehicle systems (for example: the system sets a classification condition of "car group" under the car system, the car group comprises car chassis number, car and production year, the production year comprises from the minimum production year to the maximum production year, the car chassis number and the car number are divided into the same car group and the minimum production year and the maximum production year of the car group are displayed, by setting the vehicle groups, 62 combinations of the vehicle types, the production year, the displacement and the chassis number above can be divided into 3 vehicle groups (as shown in fig. 2, three vehicle groups such as ' Fox three-carriage (C307 2005-2012) '), and the corresponding displacement below each vehicle group), for the whole ' Fox ' vehicle system, the user selection times and the difficulty are greatly simplified after the vehicle groups are divided according to the vehicle groups, as shown in fig. 1, the ' Fox three-carriage (C307 2005-2012) ', ' Fox three-carriage (C346 2012-8), ' Fox three-carriage (C519 2018-2021), ' Fox-two-carriage (C307 2006-2012), ' Fox-two-carriage (C467 2012-2020), ' Fox-two-carriage (C519 2018-2021), ' Fox-Active (C519 2019-2021), ' 7 vehicle groups are arranged below Fox- & gt, and each vehicle group can be selected in a small vehicle type range of one time according to the requirements of the user, and the displacement of the vehicle types can be selected in a small vehicle type range of one time.
The search box module is used for inputting keywords by a user and matching the keywords with fields of a vehicle type database, the selection box module is used for displaying catalogues of fields such as brands, manufacturers, vehicle systems, vehicle groups, displacement and the like in the vehicle type database and is used for selection by a user, the selection box module comprises a first selection box module, a second selection box module, a third selection box module, a fourth selection box module and a fifth selection box module, the first selection box module is used for displaying the brands catalogues of the brands and is used for selection by the user (leftmost selection box in the figure 1), the second selection box module is used for displaying the catalogues of the manufacturers and is used for selection by the user (leftmost second selection box in the figure 1), the third selection frame module is used for displaying the train catalog of the train and is used for user selection (the third selection frame on the left side in fig. 1), the fourth selection frame module is used for displaying the train catalog of the train set and is used for user selection (the fourth selection frame on the left side in fig. 1), the fifth selection frame module is used for displaying the displacement catalog of the train set and is used for user selection (the right-most selection frame in fig. 1), the field brands, manufacturers, trains, the train sets and the displacement in the train type database are classified layer by layer (the background classification of the database), the hierarchical structure of the next-level catalog is formed, the manufacturer catalog is a subdirectory of the brand catalog, the train catalog is a subdirectory of the manufacturer catalog, the train catalog is a subdirectory of the train catalog, and the displacement catalog is a subdirectory of the train catalog. When the search box module keyword is matched with a field in the vehicle model database, when one of the brand catalog, the manufacturer catalog, the train catalog, the group catalog or the displacement catalog is displayed, all the catalogs on the upper level and adjacent subdirectories are displayed simultaneously, for example: searching for the Ford keyword, wherein the first selection frame module displays a brand catalog, and the second selection frame module displays a manufacturer order; searching a keyword of 'Changan Ford', wherein the first selection frame module displays a brand catalog, the second selection frame module displays a manufacturer catalog, and the third selection frame module displays a train catalog; searching for the key word 'Focus', wherein the first selection frame module displays a brand catalog, the second selection frame module displays a manufacturer catalog, the third selection frame module displays a train catalog, and the fourth selection frame module displays a catalog of the train set, so that a user can select from the middle according to the input key word, and refine the vehicle types to be searched to a range with a smaller number.
The brand catalogue is ordered according to a preset brand spelling initial rule, wherein the brand spelling initial rule is the brand spelling initial ascending order.
The system also comprises a display frame module (the display frame module can be arranged below the same page of the search frame module), the display frame module is used for displaying a plurality of vehicle types in the vehicle type database after being screened by the selection frame module, the vehicle types displayed by the display frame module are ordered according to the descending order of the holding quantity of the vehicle types, the vehicle types with larger holding quantity are arranged at the position which is more forward, when one page of interface can not display all the vehicle types, the display frame module can enter the working state after the catalogue of the group of the fourth selection frame module is selected by a user, namely, the screened vehicle types are displayed, so that the number of the vehicle types displayed on the page is less, a client can directly select the desired vehicle types in the display frame module, when the number of the vehicle types is more, the displacement of the fifth selection frame module can be continuously selected, the information of the vehicle types displayed in the display frame module is refreshed, the number of the vehicle types after being screened by the displacement is less, the range is more accurate, and the user selects the desired vehicle types in the display frame module; the display frame module can also enter a working state when any one of the first selection frame module, the second selection frame module or the third selection frame module is selected by a user, the number of vehicle types displayed by the display frame module is large at the moment, along with the click selection of the next-stage subdirectory in the selection frame module by the user, the vehicle type information in the display frame module is refreshed and screened along with the refreshing, the number of screened vehicle types is continuously reduced, the range is smaller and smaller, and the user can conveniently select the wanted vehicle type.
As shown in fig. 1 and fig. 3, in the embodiment of the present invention, a method for intelligently searching vehicle types based on a vehicle group takes a certain vehicle type in which a user wants to search for chant ford foss in the system of the present invention as an example, and includes the following steps:
Step 1: keywords entered by a user in a search box; (keyword is input in the model information frame in FIG. 1)
Step 2: classifying a plurality of vehicle types in a vehicle type database layer by layer (database background classification) according to brands, manufacturers, vehicle systems, vehicle groups and displacement to form five-level catalogs which are brand catalogs, manufacturer catalogs, vehicle system catalogs, vehicle group catalogs and displacement catalogs of the sub-catalogs of the previous layer at the next level, matching the keywords in the step 1 with fields of the brands, manufacturers, vehicle systems, vehicle groups and displacement in the vehicle type database, and selecting layer by layer:
Step 2.1: when the keyword is a word segment matched with a brand, displaying a brand catalog and a manufacturer catalog, marking the brand related to the keyword, selecting the manufacturer catalog of the next stage for a user, and selecting the manufacturer catalog layer by layer until the displacement catalog is selected; (entering the keyword "Ford", the first selection box module displaying the brand catalog with the "Ford" brand being marked, the second selection box module displaying the three manufacturer's catalogs "Jiangling Ford", "Inlet Ford" and "Changan Ford" for customer selection)
Step 2.2: when the keyword is word segment matched to the manufacturer, displaying brand catalogs, manufacturer catalogs and car catalogs, marking brands and manufacturers related to the keyword, selecting car catalogs of the next stage for users, and selecting the car catalogs layer by layer until the displacement catalogs are selected; (the key word "Changan Fud" is input, the first selection frame module displays a brand catalog in which the "Fud" brand is marked, the second selection frame module displays a manufacturer catalog in which the "Changan Fud" is marked, and the third selection frame module displays a plurality of train catalogs such as "Carnival", "seeker", "Fukes" and the like for customers to select)
Step 2.3: when the keyword is a word segment matched with the train, displaying a brand catalog, a manufacturer catalog, a train catalog and a train catalog, marking brands, manufacturers and trains related to the keyword, selecting the train catalog of the next stage for a user, and selecting the train catalog layer by layer until the displacement catalog is selected; (entering the keyword "Focus", the first selection box module displaying a brand catalog wherein "Ford" brands are marked, the second selection box module displaying a manufacturer catalog wherein "Changan Ford" is marked, the third selection box module displaying a plurality of train catalogs wherein "Focus" is marked, the fourth selection box module displaying a consist catalog for selection by the user)
Step 2.4: when the keyword is a word segment matched with the train set, displaying a brand directory, a manufacturer directory, a train set directory and a displacement directory, marking brands, manufacturers, train sets and train sets related to the keyword, and selecting the displacement directory of the next stage for a user; the brand, the manufacturer and the train are in the existing classification mode, the train is classified according to the train under the same brand and the same manufacturer, the train comprises data of automobile chassis numbers, automobile algebra and production years, the production years comprise data from the minimum production year to the maximum production year, the automobile chassis numbers and the automobile algebra are divided into the same train, the minimum production year and the maximum production year of the train are displayed, when the key words are matched with any field of the automobile chassis numbers, the automobile algebra and the production year of the train, the train catalog is directly displayed, the corresponding train is marked (the key words of 'Fox-three boxes' or 'Fox-C346' or 'Fox-three boxes-2016' or 'Fox-2016' are input), the first selection box module displays a brand catalog in which "ford" brands are marked, the second selection box module displays a manufacturer catalog in which "Changan Ford" is marked, the third selection box module displays a plurality of train catalogs in which "Focus" is marked, and the fourth selection box module displays a plurality of train set catalogs in which a train set related to an input keyword is marked, and when a plurality of train sets are related simultaneously, a plurality of train sets are marked simultaneously, for example, "Fox-2016" is input, and two train sets satisfying conditions, "Fox-three (C3462012-2018)" and "Fox-two (C4672012-2020)" in FIG. 1 are marked simultaneously.
Step 2.5: when the keyword is a multi-word segment, the multi-field keywords are respectively matched after being split, the matching process is the same as the word segments from the step 2.1 to the step 2.4, and the weight value size sequence of the hit field of the keyword is as follows: the method comprises the steps that a vehicle group > displacement > vehicle system > manufacturer > brand, then one result with the largest weight value in the hit brand, manufacturer, vehicle system, vehicle group or displacement is displayed, the catalog corresponding to the result is displayed, a plurality of superior catalogs and next-level subdirectories of the catalog corresponding to the result are displayed at the same time, the next-level subdirectories are selected by a user, and the next-level subdirectories are selected layer by layer until the displacement catalogs are selected; for example: the input keyword is 'Length An Fute Fox Sancar 2016', after splitting, the two directories can be matched with the field and the corresponding directory is displayed, only the directory matched with the train set is displayed according to the weight value order, and the directory result is displayed in the same step 2.4.
Step 3: and (3) displaying screening results in the vehicle model database in a display frame module according to the selection of the client in the step (2), and arranging the screening results in descending order according to the numerical value of the vehicle model holding quantity. For example: after matching and selection, 3 specific vehicle types are arranged under the condition of 1.5T displacement of a 'Fox-three carriage (C3462012-2018)' vehicle group, wherein the vehicle types 1, 2 and 3 are displayed in a display frame module for selection by a user, and the vehicles can be distinguished from cold doors and vehicle doors by the user according to descending numerical values of the vehicle types.
Because the number of the displayed vehicle types is too large as many as thousands of vehicle types corresponding to each brand or the vehicle system of the same brand, the number of the displayed vehicle types can be too large when the brand is selected first, and in order to simplify the number of the vehicle types displayed by the display frame module in the step 3, the screening result in the vehicle type database can be displayed in the display frame module only after the user enters the hierarchical selection of the catalogue of the vehicle group, so that the display interface is simplified.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (9)
1. The method for intelligently searching the vehicle type based on the vehicle group is characterized by comprising the following steps of:
step 1: acquiring keywords input by a user;
Step 2: the method comprises the steps that a plurality of vehicle types in a vehicle type database are classified level by level according to brands, manufacturers, vehicle systems, vehicle groups and displacement, five levels of brand catalogs, manufacturer catalogs, vehicle system catalogs, vehicle group catalogs and displacement catalogs of the sub-catalogs of the previous level are formed in the next level, keywords in the step 1 are matched with fields of the brands, the manufacturers, the vehicle systems, the vehicle groups and the displacement in the vehicle type database, and the steps are selected level by level:
Step 2.1: when the keyword is a word segment matched with a brand, displaying a brand catalog and a manufacturer catalog, marking the brand related to the keyword, selecting the manufacturer catalog of the next stage for a user, and selecting the manufacturer catalog layer by layer until the displacement catalog is selected;
step 2.2: when the keyword is word segment matched to the manufacturer, displaying brand catalogs, manufacturer catalogs and car catalogs, marking brands and manufacturers related to the keyword, selecting car catalogs of the next stage for users, and selecting the car catalogs layer by layer until the displacement catalogs are selected;
Step 2.3: when the keyword is a word segment matched with the train, displaying a brand catalog, a manufacturer catalog, a train catalog and a train catalog, marking brands, manufacturers and trains related to the keyword, selecting the train catalog of the next stage for a user, and selecting the train catalog layer by layer until the displacement catalog is selected;
Step 2.4: when the keyword is a word segment matched with the train set, displaying a brand directory, a manufacturer directory, a train set directory and a displacement directory, marking brands, manufacturers, train sets and train sets related to the keyword, and selecting the displacement directory of the next stage for a user;
Step 2.5: when the keyword is a multi-word segment, splitting the multi-field keyword and then respectively matching, wherein the weight value order of the hit field of the keyword is as follows: the method comprises the steps that a vehicle group > displacement > vehicle system > manufacturer > brand, then one result with the largest weight value in the brand, manufacturer, vehicle system, vehicle group or displacement is hit, a catalog corresponding to the result is displayed, a plurality of superior catalogs and next-level subdirectories of the catalog corresponding to the result are displayed at the same time, the next-level subdirectories are selected by a user, and the next-level subdirectories are selected layer by layer until the displacement catalogs are selected;
Step 3: displaying screening results in a vehicle model database in a display frame module according to the selection of a customer in the step 2, and arranging the screening results in descending order according to the numerical value of the vehicle model;
in step 2, the vehicle groups are classified according to the vehicle groups under the same vehicle system under the same brand and the same manufacturer, the vehicle groups comprise data of chassis numbers, algebra and production years, the vehicle types with the same chassis numbers and algebra are classified into the same vehicle group, the minimum production year and the maximum production year of the vehicle group are displayed, and when the keywords are matched with any field of the chassis numbers, the algebra and the production year of the vehicle group, the vehicle group catalogue is directly displayed and the corresponding vehicle group is marked.
2. The method for intelligently searching vehicle types based on the vehicle group according to claim 1, wherein in the step 3, the screening result in the vehicle type database is displayed in the display frame module only after the user enters the hierarchical selection of the vehicle group catalog.
3. A vehicle group-based intelligent vehicle model searching system for realizing the method based on the vehicle group intelligent vehicle model searching according to any one of claims 1-2, which is characterized by comprising a vehicle model database, a search frame module and a selection frame module, wherein the vehicle model database comprises a plurality of vehicle models, the plurality of vehicle models are classified by brands, manufacturers, vehicle systems and displacement, the vehicle systems are classified by vehicle groups, the vehicle group comprises a vehicle chassis number, a vehicle algebra and a production year, the vehicle models with the same vehicle chassis number and the same vehicle algebra are divided into the same vehicle group and display the minimum production year and the maximum production year of the vehicle group, the selection frame module is used for displaying a catalog of the vehicle model database for a user to select and screening the plurality of vehicle models of the vehicle model database, and the search frame module is used for inputting keywords by the user and matching the keywords to the vehicle model database.
4. The consist-based intelligent vehicle model retrieval system of claim 3, wherein the selection box modules include a first selection box module for displaying the brand catalog of the brand and for selection by a user, a second selection box module for displaying the manufacturer catalog of the manufacturer and for selection by a user, a third selection box module for displaying the consist catalog of the consist and for selection by a user, and a fourth selection box module for displaying the consist catalog of the consist and for selection by a user.
5. The consist-based intelligent vehicle model retrieval system of claim 4, wherein the manufacturer catalog is a subdirectory of a brand catalog, the consist catalog is a subdirectory of a manufacturer catalog, and the consist catalog is a subdirectory of a consist catalog.
6. The consist-based intelligent retrieval vehicle model system of claim 4, wherein the selection box module further comprises a fifth selection box module for displaying a displacement catalog of the displacements for selection by a user, the displacement catalog being a sub-catalog of a consist catalog.
7. The consist-based intelligent vehicle model retrieval system of claim 6, wherein when one of the brand inventory, manufacturer inventory, train inventory, consist inventory, or displacement inventory is displayed, all of its superordinate inventory and adjacent subdirectories are displayed simultaneously.
8. The consist-based intelligent retrieval vehicle model system of claim 4, wherein the brand catalogue is ordered according to a pre-set brand pinyin initial rule, the brand pinyin initial rule being an ascending order of brand pinyin initials.
9. The intelligent vehicle model retrieval system based on the vehicle group according to claim 3, further comprising a display frame module, wherein the display frame module is used for displaying a plurality of vehicle models in the vehicle model database after being screened by the selection frame module, and the plurality of vehicle models displayed by the display frame module are ordered according to the vehicle model preservation amount descending order.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110524992.8A CN113849695B (en) | 2021-05-13 | 2021-05-13 | Method and system for intelligently searching vehicle types based on vehicle groups |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110524992.8A CN113849695B (en) | 2021-05-13 | 2021-05-13 | Method and system for intelligently searching vehicle types based on vehicle groups |
Publications (2)
Publication Number | Publication Date |
---|---|
CN113849695A CN113849695A (en) | 2021-12-28 |
CN113849695B true CN113849695B (en) | 2024-05-03 |
Family
ID=78973007
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110524992.8A Active CN113849695B (en) | 2021-05-13 | 2021-05-13 | Method and system for intelligently searching vehicle types based on vehicle groups |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113849695B (en) |
Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6324534B1 (en) * | 1999-09-10 | 2001-11-27 | Requisite Technology, Inc. | Sequential subset catalog search engine |
KR20060103165A (en) * | 2005-03-23 | 2006-09-28 | 조광현 | Classified web sites search system and method |
WO2007045671A1 (en) * | 2005-10-18 | 2007-04-26 | Swisscube Limited | Method and system for unified search using categories and keywords |
JP2011065627A (en) * | 2009-08-21 | 2011-03-31 | Yahoo Japan Corp | Information display device, display control method, and program |
CN102591890A (en) * | 2011-01-17 | 2012-07-18 | 腾讯科技(深圳)有限公司 | Method for displaying search information and search information display device |
CN102799595A (en) * | 2011-05-27 | 2012-11-28 | 赵强 | Method for searching database |
CN106202398A (en) * | 2016-07-08 | 2016-12-07 | 北京易车互联信息技术有限公司 | A kind of method and device indexing foundation |
CN107357491A (en) * | 2017-07-14 | 2017-11-17 | 深圳易嘉恩科技有限公司 | The page interaction browsed for bill document information |
CN108491447A (en) * | 2018-02-23 | 2018-09-04 | 政采云有限公司 | Optimization method and system based on cascade selector search result option |
CN108647276A (en) * | 2015-05-11 | 2018-10-12 | 何杨洲 | A kind of searching method |
CN112667700A (en) * | 2019-10-16 | 2021-04-16 | 北京航天长峰科技工业集团有限公司 | Government affair big data super search system |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2001075728A1 (en) * | 2000-03-30 | 2001-10-11 | I411, Inc. | Methods and systems for enabling efficient retrieval of data from data collections |
US6938038B2 (en) * | 2002-06-04 | 2005-08-30 | Sap Aktiengesellschaft | Method and apparatus for generating and utilizing qualifiers and qualified taxonomy tables |
US20050125261A1 (en) * | 2003-12-09 | 2005-06-09 | Alexander Omeed Adegan | Intelligent used parts cross-referencing, search and location software application |
US10776850B2 (en) * | 2016-05-18 | 2020-09-15 | Glenn E. Staats | Automated operation of automobile parts eStores with automated selection of parts and dynamic pricing |
-
2021
- 2021-05-13 CN CN202110524992.8A patent/CN113849695B/en active Active
Patent Citations (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6324534B1 (en) * | 1999-09-10 | 2001-11-27 | Requisite Technology, Inc. | Sequential subset catalog search engine |
KR20060103165A (en) * | 2005-03-23 | 2006-09-28 | 조광현 | Classified web sites search system and method |
WO2007045671A1 (en) * | 2005-10-18 | 2007-04-26 | Swisscube Limited | Method and system for unified search using categories and keywords |
JP2011065627A (en) * | 2009-08-21 | 2011-03-31 | Yahoo Japan Corp | Information display device, display control method, and program |
CN102591890A (en) * | 2011-01-17 | 2012-07-18 | 腾讯科技(深圳)有限公司 | Method for displaying search information and search information display device |
CN102799595A (en) * | 2011-05-27 | 2012-11-28 | 赵强 | Method for searching database |
CN108647276A (en) * | 2015-05-11 | 2018-10-12 | 何杨洲 | A kind of searching method |
CN106202398A (en) * | 2016-07-08 | 2016-12-07 | 北京易车互联信息技术有限公司 | A kind of method and device indexing foundation |
CN107357491A (en) * | 2017-07-14 | 2017-11-17 | 深圳易嘉恩科技有限公司 | The page interaction browsed for bill document information |
CN108491447A (en) * | 2018-02-23 | 2018-09-04 | 政采云有限公司 | Optimization method and system based on cascade selector search result option |
CN112667700A (en) * | 2019-10-16 | 2021-04-16 | 北京航天长峰科技工业集团有限公司 | Government affair big data super search system |
Also Published As
Publication number | Publication date |
---|---|
CN113849695A (en) | 2021-12-28 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN101246499B (en) | Network information search method and system | |
US8214361B1 (en) | Organizing search results in a topic hierarchy | |
Zhang et al. | Topic cube: Topic modeling for olap on multidimensional text databases | |
US20060161545A1 (en) | Method and apparatus for ordering items within datasets | |
CN106202248B (en) | Phrase-based search in information retrieval system | |
KR101190230B1 (en) | Phrase identification in an information retrieval system | |
CN111078868A (en) | Knowledge graph analysis-based equipment test system planning decision method and system | |
US20090198693A1 (en) | Method and apparatus for ordering items within datasets | |
CN102968465B (en) | Network information service platform and the search service method based on this platform thereof | |
US20130091162A1 (en) | Data Access Using Multilevel Selectors and Contextual Assistance | |
CN101308493B (en) | Entity relation exhibition method and system | |
WO2004097671A2 (en) | A system and method for generating refinement categories for a set of search results | |
Zhang et al. | Topic modeling for OLAP on multidimensional text databases: topic cube and its applications | |
CN103577489A (en) | Method and device of searching web browsing history | |
EP1869581A2 (en) | Data storage and retrieval | |
US20080059432A1 (en) | System and method for database indexing, searching and data retrieval | |
CN101320387A (en) | Web page text and image ranking method based on user caring time | |
CN103955514A (en) | Image feature indexing method based on Lucene inverted index | |
CN102937985B (en) | A kind of websites collection method for optimization analysis based on user's mental model | |
CN115391495A (en) | Method, device and equipment for searching keywords in Chinese context | |
US20140101147A1 (en) | Search | |
CN113849695B (en) | Method and system for intelligently searching vehicle types based on vehicle groups | |
CN103034709B (en) | Retrieving result reordering system and method | |
CN102216928B (en) | Method and system for retrieving data and displaying content density of a data storage | |
US10089410B2 (en) | For acceleration of pathway selection, application, and ranking in a hybrid network |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |