CN109544276B - Product model selection method and processor - Google Patents
Product model selection method and processor Download PDFInfo
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- CN109544276B CN109544276B CN201811280313.1A CN201811280313A CN109544276B CN 109544276 B CN109544276 B CN 109544276B CN 201811280313 A CN201811280313 A CN 201811280313A CN 109544276 B CN109544276 B CN 109544276B
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- 238000010187 selection method Methods 0.000 title claims abstract description 15
- 238000000034 method Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 5
- 206010063385 Intellectualisation Diseases 0.000 abstract 1
- 230000006399 behavior Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- PCTMTFRHKVHKIS-BMFZQQSSSA-N (1s,3r,4e,6e,8e,10e,12e,14e,16e,18s,19r,20r,21s,25r,27r,30r,31r,33s,35r,37s,38r)-3-[(2r,3s,4s,5s,6r)-4-amino-3,5-dihydroxy-6-methyloxan-2-yl]oxy-19,25,27,30,31,33,35,37-octahydroxy-18,20,21-trimethyl-23-oxo-22,39-dioxabicyclo[33.3.1]nonatriaconta-4,6,8,10 Chemical compound C1C=C2C[C@@H](OS(O)(=O)=O)CC[C@]2(C)[C@@H]2[C@@H]1[C@@H]1CC[C@H]([C@H](C)CCCC(C)C)[C@@]1(C)CC2.O[C@H]1[C@@H](N)[C@H](O)[C@@H](C)O[C@H]1O[C@H]1/C=C/C=C/C=C/C=C/C=C/C=C/C=C/[C@H](C)[C@@H](O)[C@@H](C)[C@H](C)OC(=O)C[C@H](O)C[C@H](O)CC[C@@H](O)[C@H](O)C[C@H](O)C[C@](O)(C[C@H](O)[C@H]2C(O)=O)O[C@H]2C1 PCTMTFRHKVHKIS-BMFZQQSSSA-N 0.000 description 1
- 238000004378 air conditioning Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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Abstract
The invention discloses a product model selection method and a processor, wherein the product model selection method comprises the following steps: step 1, inputting a type selection condition by a user; step 2, selecting the type selection result with the highest heat corresponding to the type selection condition from a sample library; and 3, determining whether the model selection result is in accordance by the user, if so, increasing the heat of the model selection result and updating the heat into the sample library. The invention memorizes and stores the model selection behavior of the user, enables the user to input the same model selection condition later, can automatically give the previous selection of the user, improves the model selection efficiency, and enables the model selection software to learn autonomously to realize intellectualization.
Description
Technical Field
The invention relates to a product type selection method and a processor for executing a computer program corresponding to the product type selection method.
Background
With the development of science and technology, the updating of products is more and more frequent, and products of different series and different models are continuously released, so that the types of the products are very many. Taking an air conditioner as an example, when a user selects the models of the indoor unit and the outdoor unit by using the model selection software, the model selection software needs to meet the model selection requirements of a large number of user groups, the requirements on the series and the models of air conditioner products need to be comprehensively covered in terms of product classification, and the requirements are strictly followed in terms of model selection logic. Based on the two basic requirements, the following conditions often occur when a user uses software by using popular model selection software which covers product models purely and comprehensively and strictly follows the model selection requirements:
1. Zero stock of the air conditioner products selected;
2. due to the fact that the updating iteration speed of the air conditioner products is different in each area due to factors such as economy and the like, eliminated products or brand-new products are selected in some areas.
The method and the device have the advantages that more energy and time are consumed for the user to select the appropriate type selection result, the type selection logic is single and rigid, and even if the product selected last time does not meet the user requirement, the product which does not meet the user requirement can be recommended when the type is selected again next time.
Disclosure of Invention
In order to solve the problem that the selection software in the prior art cannot memorize the user behavior, so that the user needs to spend more energy and time for selecting the type each time, the invention provides a product selection method, which comprises the following steps:
step 1, inputting a type selection condition by a user;
step 2, selecting the type selection result with the highest heat corresponding to the type selection condition from a sample library;
and 3, determining whether the model selection result is in accordance by the user, if so, increasing the heat of the model selection result and updating the heat into the sample library.
Preferably, if no type selection result corresponding to the type selection condition exists in the sample library, the following steps are executed:
step 2.1, selecting a new type selection result corresponding to the type selection condition from a database;
And 3.1, determining whether the model selection result is in accordance by the user, and updating the new model selection result and the heat to the sample library if the model selection result is in accordance.
Further, in the step 3 or the step 3.1, if the user determines that the model selection result does not meet the specification, it is determined whether the model selection result is from a sample library, and if the model selection result is from the sample library, the step 2.1 is executed; otherwise, manually selecting the type by the user, and updating the type selection result of the manual type selection and the heat degree thereof to the sample library.
Further, in the step 3 or the step 3.1, if the user determines that the type selection result does not meet, the user may set the type selection result as not selectable.
Further, in the step 3 or the step 3.1, if the user determines that the model selection result does not meet the criteria and the model selection result comes from the sample library, the step 2.1 is executed while reducing the heat of the model selection result and updating the heat to the sample library.
Preferably, the sample library corresponds to the user one by one, and the database is a set containing all the type selection results.
Preferably, the sample repository is provided on a local computer. The database is located on a remote server.
In this embodiment, the heat is the number of times of selection.
In particular applications, the product may be an air conditioner. The model selection conditions comprise engineering working condition conditions, load requirements and the like.
The invention further provides a processor for executing a computer program, wherein the computer program is used for executing the product model selection method in the technical scheme.
Compared with the prior art, the method and the system can enable each user to filter and screen respective model selection products, avoid the products from being selected and not meet the requirements of the users; and the model selection result of each user is subjected to statistical analysis to generate an independent sample library, the product range frequently selected by the user is accurately locked, the accurate model selection is realized, and the model selection experience and the model selection efficiency of the user are improved.
Drawings
The invention is described in detail below with reference to embodiments and the attached drawings, wherein:
FIG. 1 is a flow chart of one embodiment of the present invention.
Detailed Description
The principle of the present invention will be described in detail below with reference to the air conditioning unit model selection software as a specific embodiment.
The product type selection method of the invention is characterized in that a sample library is arranged on a local computer, the sample library corresponds to the user one by one and is used for memorizing and storing the past type selection behaviors of the user, so that the user can accurately and efficiently provide the corresponding type selection result for the user when repeatedly operating. And meanwhile, a database is also arranged and is a set containing all the type selection results.
When the user inputs the type selection conditions (including engineering working condition conditions, load requirements, and the like), the type selection result with the highest heat corresponding to the type selection conditions is selected in the sample library, and in this embodiment, the number of times selected by the user is used as the heat, and when the type selection conditions are the same, the type selection result most frequently selected by the user is automatically provided to the user.
And if the user determines that the type selection result is in accordance with the user selection result, increasing the heat of the type selection result and updating the heat into the sample library. If the user considers that the type selection result is not matched, reducing the heat of the type selection result and updating the heat into a sample library. Meanwhile, the user is provided with a choice to set the type selection result as non-selectable, for example, all types have ABCDE five-type products, the user A sets the CD type product as non-selectable, and the user B sets the E type product as non-selectable. When checking the product model, the user A only can check the model ABE, the user B only can check the model ABCD, and meanwhile, products with the models which are not selectable do not participate in model selection recommendation. Alternatively, if the user selects not to select, the type selection result may be deleted from the sample library.
And then, continuously searching a corresponding new type selection result from a database on the remote server according to the type selection condition input by the user, determining whether the type selection result is in accordance with the user, and if so, updating the new type selection result and the heat degree thereof into the sample library. If not, the user selects the type manually, and the type selection result and the heat of the manual type selection are updated to the sample library.
Through the model selection method, the user can filter and screen the model selection products, and only the products owned by the user are recommended when the model selection is recommended. And the model selection result of the user is subjected to statistical analysis to generate a sample library, and when the user selects the model again, the model which is in accordance with the model selection logic and is selected by the user for many times is preferentially recommended, so that the model selection efficiency of the user is improved. Besides air conditioners, other product types are also within the protection scope of the invention, and the invention also protects a processor used for executing a computer program corresponding to the product type selection method.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (8)
1. A product model selection method, comprising:
step 1, inputting a type selection condition by a user;
step 2, if the model selection result corresponding to the model selection condition exists in the sample library, selecting the model selection result with the highest heat corresponding to the model selection condition from the sample library, and executing the step 3; if the model selection result corresponding to the model selection condition does not exist in the sample library, executing the following steps:
Step 2.1, selecting a new type selection result corresponding to the type selection condition from a database;
step 3.1, the user determines whether the new model selection result is in line, if so, the new model selection result and the heat are updated to a sample library, and the flow is ended;
step 3, the user determines whether the model selection result is in accordance, if so, the heat of the model selection result is increased and the model selection result is updated to a sample library;
in the step 3 or the step 3.1, if the user determines that the model selection result does not conform to the model selection result and the model selection result comes from the sample library, the step 2.1 is executed, and meanwhile, the heat of the model selection result is reduced and updated to the sample library;
the sample library corresponds to the user one by one, and the heat of the type selection result of the sample library is the times selected by the user.
2. The product model selection method according to claim 1, wherein in step 3 or step 3.1, if the user determines that the model selection result does not meet, it is determined whether the model selection result comes from a sample library, and if the model selection result comes from the sample library, the step 2.1 is executed; otherwise, manually selecting the type by the user, and updating the type selection result of the manual type selection and the heat degree thereof to the sample library.
3. A product typing method according to claim 2, wherein in step 3 or step 3.1, if the user determines that the typing results are not satisfactory, the user may set the typing results as non-selectable.
4. The product typing method according to claim 1, wherein said sample library is provided on a local computer.
5. The product typing method according to claim 1, wherein said database is provided on a remote server.
6. The product model selection method according to any one of claims 1 to 5, wherein the product is an air conditioner.
7. A product model selection method as claimed in claim 6, characterized in that the model selection conditions comprise engineering conditions and load requirements.
8. A processor for executing a computer program for performing the method of product selection according to any one of claims 1 to 7.
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| CN201811280313.1A CN109544276B (en) | 2018-10-30 | 2018-10-30 | Product model selection method and processor |
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| CN201811280313.1A CN109544276B (en) | 2018-10-30 | 2018-10-30 | Product model selection method and processor |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120246029A1 (en) * | 2011-03-25 | 2012-09-27 | Ventrone Mark D | Product comparison and selection system and method |
| CN102930019A (en) * | 2012-11-02 | 2013-02-13 | 沈阳建筑大学 | Type selection method and sample database of fans |
| CN103425712A (en) * | 2012-05-25 | 2013-12-04 | 珠海格力电器股份有限公司 | Engineering data processing method and system for engineering model selection |
| CN104123284A (en) * | 2013-04-24 | 2014-10-29 | 华为技术有限公司 | Recommendation method and server |
| CN107341181A (en) * | 2017-05-27 | 2017-11-10 | 武汉斗鱼网络科技有限公司 | Method, apparatus, computer-readable recording medium and computer equipment are recommended in search |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120246029A1 (en) * | 2011-03-25 | 2012-09-27 | Ventrone Mark D | Product comparison and selection system and method |
| CN103425712A (en) * | 2012-05-25 | 2013-12-04 | 珠海格力电器股份有限公司 | Engineering data processing method and system for engineering model selection |
| CN102930019A (en) * | 2012-11-02 | 2013-02-13 | 沈阳建筑大学 | Type selection method and sample database of fans |
| CN104123284A (en) * | 2013-04-24 | 2014-10-29 | 华为技术有限公司 | Recommendation method and server |
| CN107341181A (en) * | 2017-05-27 | 2017-11-10 | 武汉斗鱼网络科技有限公司 | Method, apparatus, computer-readable recording medium and computer equipment are recommended in search |
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