CN113570428B - System for be used for online commodity uniformity screening - Google Patents
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- CN113570428B CN113570428B CN202110833914.6A CN202110833914A CN113570428B CN 113570428 B CN113570428 B CN 113570428B CN 202110833914 A CN202110833914 A CN 202110833914A CN 113570428 B CN113570428 B CN 113570428B
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- 238000012216 screening Methods 0.000 title claims abstract description 19
- 238000012545 processing Methods 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000013138 pruning Methods 0.000 claims description 4
- 230000035945 sensitivity Effects 0.000 claims description 4
- 230000010365 information processing Effects 0.000 abstract description 2
- 230000006870 function Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- DWDGSKGGUZPXMQ-UHFFFAOYSA-N OPPO Chemical compound OPPO DWDGSKGGUZPXMQ-UHFFFAOYSA-N 0.000 description 1
- 244000062793 Sorghum vulgare Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 235000019713 millet Nutrition 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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- G—PHYSICS
- 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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- 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
- G06F16/9027—Trees
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- 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
- G06F16/90335—Query processing
- G06F16/90348—Query processing by searching ordered data, e.g. alpha-numerically ordered data
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- 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
- G06F16/906—Clustering; Classification
Abstract
The invention discloses a system for online commodity consistency screening, which belongs to the field of electronic commerce information processing, and comprises the steps of firstly constructing classification tables and attribute classification tables of all commodity category names, storing the classification tables into a database, and then constructing a consistency screening system according to the classification tables; the classification forest is composed of a plurality of classification trees of commodity categories, each classification tree is used for determining commodity codes of one class of commodity, and when the classification forest contains all commodities, unique codes of all commodity categories are determined. The invention can have certain generalization capability on unknown commodity information by constructing the classification tree, can correctly screen the consistency of commodities and improves the processing efficiency.
Description
Technical Field
The invention belongs to the field of electronic commerce information processing, and particularly relates to a system for online commodity consistency screening.
Background
The commodity classification can be carried out on the commodity on the electronic commerce platform, but the classification and the structure of the commodity on different sales platforms are often different, and the commodity statistics is carried out uniformly when the commodity information is determined for large-quantity and various platform data.
For market analysts in the product side, if the consistency of the commodities on all the sales platforms can be determined, the sales conditions of the commodities can be counted rapidly for the specific commodities, and the sales and market control of the products are facilitated. For the consistency of the commodities, the information of the commodities on the platform of the selling electric vendor needs to be analyzed, and the commodity description information is completely classified, so that the unique code of the commodities is determined, and the uniqueness of the commodities on multiple platforms can be determined.
Disclosure of Invention
Aiming at the technical problems, the invention provides a system for online commodity consistency screening, which can calculate commodity characteristics on an e-commerce platform and output unique codes of all kinds of commodities.
In order to solve the technical problems, the invention adopts the following technical scheme: a system for online merchandise uniformity screening, comprising: firstly, constructing a classification table and an attribute classification table of all commodity category names, storing the classification table and the attribute classification table into a database, and then constructing a consistency screening system according to the classification table, wherein the specific steps of constructing the consistency screening system are as follows:
step S10: firstly, acquiring a commodity classification label of an e-commerce platform, inquiring whether the classification label exists in a classification table, and if the classification label does not exist, inserting the classification label into the classification table; if the classification label exists, continuing to acquire the commodity attribute of the classification label, and dividing the commodity attribute into a plurality of dimensions according to attribute characteristics, wherein each attribute forms one dimension;
step S20: calculating weight according to the commodity classification label grade, and calculating attribute priority sequence numbers in combination with commodity attributes;
step S30: acquiring commodity categories and commodity attributes from the sub-list, respectively constructing classification trees by taking commodities of different categories as root nodes and commodity attribute characteristics under each category, and forming a classification forest by a plurality of classification trees to form a consistency screening system;
step S40: accessing commodity addresses or system recommendation information, acquiring attribute characteristics of commodities, storing the attribute characteristics into a commodity attribute information pool, selecting attribute characteristics to be classified from the commodity attribute information pool, inputting the attribute characteristics to a system, and acquiring codes of the commodities through a classification tree in the system;
step S50: and storing the commodity codes into a system, establishing a corresponding relation between the commodity codes and the commodity, and determining the consistency of the commodity.
Further, in the step S20, the specific step method for calculating the attribute priority sequence number is as follows: firstly, carrying out hierarchical division on label grades of commodities, calculating the weight of the commodity labels through commodity label description importance, distributing the weight of the label grades from high to low, and then carrying out calculation on all the attributes of the commodities in a commodity attribute information pool; and during calculation, carrying out vectorization processing on the classification under the attribute, and determining the priority sequence number of the classification according to the sequence in the attribute classification table.
Further, when the attribute classification table is constructed, classifying characters are vectorized and converted into one-hot codes when the classification under the attribute is character type, and the sequence of the classifying characters in the classification table is determined according to the sequence of the one-hot codes in the one-hot table; when the attribute is classified into numerical values, the numerical values are arranged in an attribute classification table from small to large.
Further, the specific steps of constructing the classification tree in step S30 are as follows: taking all the categories in the commodity category classification table as root nodes, taking commodity attributes under the categories as child nodes, arranging the child nodes orderly according to the priority sequence number calculated in the step S20, and recursively constructing all the nodes in the attribute classification table in sequence until all the classification attribute features are contained in the classification tree; on the path from the parent node to the child node, a classification sequence number under the attribute is assigned.
Further, the specific implementation process of step S40 is as follows:
step S401: inputting online commodity address or system recommendation information, accessing the address, and extracting attribute characteristic information of the commodity: acquiring commodity text description information and picture description information, and storing attribute features into a commodity attribute information pool;
step S402: finding out a root node in the system according to commodity class, selecting a classification tree where the root node is located, and sequentially inputting the features in the commodity attribute information pool into the classification tree;
step S403: the method comprises the steps of setting the consistency sensitivity degree of commodities, changing the judging degree of the consistency attribute of the commodities, and pruning a classification tree according to different classification requirements, wherein attribute information which cannot describe the commodities is pruned, and leaf nodes are feature information which finally describe the commodities;
step S404: on the pruned classification tree, determining the classification attribute codes of all the attributes by the commodity attribute characteristics through the classification tree;
step S405: and acquiring codes on paths in the reclassifying tree from left to right from the root node of the commodity category to the characteristic information of the final descriptive commodity, and combining the codes on the paths to form the commodity code.
Further, the classification forest is composed of a plurality of classification trees of commodity categories, each classification tree is used for determining commodity codes of one type of commodity, and when the classification forest contains all commodities, unique codes of all commodity categories are determined.
Compared with the prior art, the invention has the beneficial effects that: (1) According to the invention, the category classification table is arranged, so that the commodity category on each platform can be subjected to full-category statistics, and a finished commodity classification table is constructed; (2) The invention can have certain generalization capability on unknown commodity information by constructing the classification tree, can correctly screen the consistency of commodities and improves the processing efficiency.
Drawings
FIG. 1 is a schematic overall flow chart of the present invention.
FIG. 2 is a schematic diagram of calculating attribute weights according to the present invention.
FIG. 3 is a flow chart of the invention for obtaining commodity codes.
Fig. 4 and 5 are schematic diagrams of classification tree and classification forest structures according to the present invention.
Detailed Description
The invention will be further described with reference to specific examples, illustrative examples and illustrations of which are provided herein to illustrate the invention, but are not to be construed as limiting the invention.
Examples: as shown in fig. 1, 2, 3, 4 and 5, a system for on-line commodity consistency screening is disclosed, firstly, a classification table and an attribute classification table of all commodity category names are constructed and stored in a database, and then a consistency screening system is constructed according to the classification table, wherein the specific steps for constructing the consistency screening system are as follows:
step S10: firstly, acquiring a commodity classification label of an e-commerce platform, inquiring whether the classification label exists in a classification table, and if the classification label does not exist, inserting the classification label into the classification table; if the classification label exists, continuing to acquire the commodity attribute of the classification label, and dividing the commodity attribute into a plurality of dimensions according to attribute characteristics, wherein each attribute forms one dimension; the positions of different classifications under each attribute are very similar in vector space, and mapping in vector space exists between the associated attributes;
step S20: calculating weight according to the commodity classification label grade, and calculating attribute priority sequence numbers in combination with commodity attributes; the classification labels on different electronic commerce platforms are different, so that the weight obtained by the class calculation of the classification labels has only a certain reference function on the commodity attribute calculation attribute priority sequence number, and the commodity attribute priority sequence number is calculated according to the characteristics of the commodity attribute;
step S30: acquiring commodity categories and commodity attributes from the sub-list, constructing classification trees by taking commodities of different categories as root nodes and commodity attribute characteristics, respectively constructing the classification trees by taking the commodity attribute characteristics of each category, and forming a classification forest by a plurality of classification trees to form a consistency screening system;
step S40: accessing commodity addresses or system recommendation information, acquiring attribute characteristics of commodities, storing the attribute characteristics into a commodity attribute information pool, selecting attribute characteristics to be classified from the commodity attribute information pool, inputting the attribute characteristics to a system, and acquiring codes of the commodities through a classification tree in the system;
step S50: and storing the commodity codes into a system, establishing a corresponding relation between the commodity codes and the commodity, and determining the consistency of the commodity.
Further, in the step S20, the specific step method for calculating the attribute priority sequence number is as follows: firstly, carrying out hierarchical division on label grades of commodities, calculating the weight of the commodity labels through commodity label description importance, distributing the weight of the label grades from high to low, then carrying out calculation on all the attributes of the commodities in a commodity attribute information pool, carrying out vectorization processing on classification under the attributes during calculation, and determining the priority sequence of classification according to the sequence in an attribute classification table.
When the attribute classification table is constructed, classifying the classified characters into character types, vectorizing and converting the classified characters into independent heat codes, and determining the sequence of the classified characters in the classification table according to the sequence of the independent heat codes in the independent heat table; when the attribute is classified into numerical values, the numerical values are arranged in an attribute classification table from small to large.
The specific steps of constructing the classification tree in step S30 are as follows: taking all the categories in the commodity category classification table as root nodes, taking commodity attributes under the categories as child nodes, arranging the child nodes orderly according to the priority sequence number calculated in the step S20, and recursively constructing all the nodes in the attribute classification table in sequence until all the classification attribute features are contained in the classification tree; on the path from the parent node to the child node, a classification sequence number under the attribute is assigned.
The specific implementation process of step S40 is as follows:
step S401: inputting online commodity address or system recommendation information, accessing the address, and extracting attribute characteristic information of the commodity: acquiring commodity text description information and picture description information, and storing attribute features into a commodity attribute information pool;
step S402: finding out a root node in the system according to commodity class, selecting a classification tree where the root node is located, and sequentially inputting the features in the commodity attribute information pool into the classification tree; the attribute feature input sequence of the commodity is calculated in the step S20, and features which can be input into the classification tree are features which play a key role in describing the commodity;
step S403: the method comprises the steps of setting the consistency sensitivity degree of commodities, changing the consistency attribute judging degree of the commodities, determining the consistency attribute judging degree of the commodities according to different classification requirements, pruning a classification tree, cutting off attribute information which cannot describe the commodities, and enabling leaf nodes to be feature information which finally describes the commodities; pruning operation is used for changing the subclasses of statistics, and can reflect the consistency problem of commodities to different degrees;
step S404: on the pruned classification tree, determining the classification attribute codes of all the attributes by the commodity attribute characteristics through the classification tree;
step S405: and acquiring codes on paths in the reclassifying tree from left to right from the root node of the commodity category to the characteristic information of the final descriptive commodity, and combining the codes on the paths to form the commodity code.
Further, the classification forest is composed of a plurality of classification trees of commodity categories, each classification tree is used for determining commodity codes of one type of commodity, and when the classification forest contains all commodities, unique codes of all commodity categories are determined.
In the implementation process of the embodiment, taking a mobile phone model as an example, the workflow of the consistency screening system is described: in the E-commerce platform, the commodity features describing the mobile phone are mobile phone brands such as Hua Cheng, millet, OPPO, vivo and the like, which are brand attributes of mobile phone category attributes, and the features describing the functions of the mobile phone are as follows: running memory, such as 3GB, 4GB, 8GB, 16GB, etc., is a numerical feature; color of the mobile phone: red, blue, black, purple, etc., are character descriptive features; the description of other additional functions is also different in classification description on different e-commerce platforms, the information is considered as a secondary priority when calculating the commodity attribute priority sequence number, and after the mobile phone information on the commodity platform is collected, a classification tree for classifying mobile phone models is constructed: when the commodity page is a mobile phone of a certain brand, the color is black, the running memory is 6GB, the network type is 5G, the characteristics formed by the commodity attributes sequentially pass through the classification tree to obtain the attribute priority sequence number of the attribute in the classification tree, when all commodity information can be classified in the classification tree, the path from the root node to the leaf node is the unique code of the attribute, and the codes are combined to be the unique code of the commodity. When the sensitivity of the consistency of the commodity is reduced, only the brand of the mobile phone is required to be confirmed, the classification tree is pruned, and the attribute describing the brand of the mobile phone is cut into leaf nodes.
The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the present invention without inventive labor, as those skilled in the art will recognize from the above-described concepts.
Claims (1)
1. A system for online merchandise uniformity screening, comprising: firstly, constructing a classification table and an attribute classification table of all commodity category names, storing the classification table and the attribute classification table into a database, and then constructing a consistency screening system according to the classification table, wherein the specific steps of constructing the consistency screening system are as follows:
step S10: firstly, acquiring a commodity classification label of an e-commerce platform, inquiring whether the classification label exists in a classification table, and if the classification label does not exist, inserting the classification label into the classification table; if the classification label exists, continuing to acquire the commodity attribute of the classification label, and dividing the commodity attribute into a plurality of dimensions according to attribute characteristics, wherein each attribute forms one dimension;
step S20: calculating weight according to the commodity classification label grade, and calculating attribute priority sequence numbers in combination with commodity attributes;
step S30: acquiring commodity categories and commodity attributes from the classification table, respectively constructing classification trees by taking commodities of different categories as root nodes and commodity attribute characteristics under each category, and forming a classification forest by a plurality of classification trees to form a consistency screening system;
step S40: accessing commodity addresses or system recommendation information, acquiring attribute characteristics of commodities, storing the attribute characteristics into a commodity attribute information pool, selecting attribute characteristics to be classified from the commodity attribute information pool, inputting the attribute characteristics to a system, and acquiring codes of the commodities through a classification tree in the system;
step S50: storing commodity codes into a system, establishing a corresponding relation between the commodity codes and the commodity, and determining the consistency of the commodity: in the step S20, the specific step method for calculating the attribute priority sequence number is as follows: firstly, carrying out hierarchical division on label grades of commodities, calculating the weight of the commodity labels through commodity label description importance, distributing the weight of the label grades from high to low, and then carrying out calculation on all the attributes of the commodities in a commodity attribute information pool; during calculation, carrying out vectorization processing on the classification under the attribute, and determining the priority sequence number of the classification according to the sequence in the attribute classification table; when the attribute classification table is constructed, classifying the classified characters into character types, vectorizing and converting the classified characters into independent heat codes, and determining the sequence of the classified characters in the classification table according to the sequence of the independent heat codes in the independent heat table; when the attribute is classified into a numerical value type, the numerical values are arranged in an attribute classification table from small to large; the specific steps of constructing the classification tree in step S30 are as follows: taking all the categories in the commodity category classification table as root nodes, taking commodity attributes under the categories as child nodes, arranging the child nodes orderly according to the priority sequence number calculated in the step S20, and recursively constructing all the nodes in the attribute classification table in sequence until all the classification attribute features are contained in the classification tree; a classification sequence number under the attribute is distributed on the path from the father node to the child node; the specific implementation process of step S40 is as follows:
step S401: inputting online commodity address or system recommendation information, accessing the address, and extracting attribute characteristic information of the commodity: acquiring commodity text description information and picture description information, and storing attribute features into a commodity attribute information pool;
step S402: finding out a root node in the system according to commodity class, selecting a classification tree where the root node is located, and sequentially inputting the features in the commodity attribute information pool into the classification tree;
step S403: the method comprises the steps of setting the consistency sensitivity degree of commodities, changing the judging degree of the consistency attribute of the commodities, and pruning a classification tree according to different classification requirements, wherein attribute information which cannot describe the commodities is pruned, and leaf nodes are feature information which finally describe the commodities;
step S404: on the pruned classification tree, determining the classification attribute codes of all the attributes by the commodity attribute characteristics through the classification tree;
step S405: acquiring codes on paths in the classification tree from left to right in sequence from a root node of the commodity category to the characteristic information of the final descriptive commodity, and combining the codes on the paths to form the commodity code; the classification forest is composed of a plurality of classification trees of commodity categories, each classification tree is used for determining commodity codes of one type of commodity, and when the classification forest contains all commodities, unique codes of all commodity categories are determined.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5179643A (en) * | 1988-12-23 | 1993-01-12 | Hitachi, Ltd. | Method of multi-dimensional analysis and display for a large volume of record information items and a system therefor |
| JP2005208709A (en) * | 2004-01-20 | 2005-08-04 | Fuji Xerox Co Ltd | Data classification processing apparatus, data classification processing method and computer program |
| CN102841946A (en) * | 2012-08-24 | 2012-12-26 | 北京国政通科技有限公司 | Commodity data retrieval sequencing and commodity recommendation method and system |
| CN102915498A (en) * | 2011-08-03 | 2013-02-06 | 腾讯科技（深圳）有限公司 | Method and device for goods classification of e-commerce platform |
| CN103593763A (en) * | 2012-08-13 | 2014-02-19 | 腾讯科技（深圳）有限公司 | An information organization method and an apparatus thereof and an information display method and an apparatus thereof |
| CN103778214A (en) * | 2014-01-16 | 2014-05-07 | 北京理工大学 | Commodity property clustering method based on user comments |
| CN103914492A (en) * | 2013-01-09 | 2014-07-09 | 阿里巴巴集团控股有限公司 | Method for query term fusion, method for commodity information publish and method and system for searching |
| CN103995905A (en) * | 2014-06-13 | 2014-08-20 | 重庆大学 | Electronic commerce content multi-dimensional classification, navigation and skipping method |
| CN107730343A (en) * | 2017-09-15 | 2018-02-23 | 广州唯品会研究院有限公司 | A kind of user's merchandise news method for pushing and equipment based on picture attribute extraction |
| KR20180123826A (en) * | 2017-05-10 | 2018-11-20 | 네모커머스(주) | Correspondences generation system of goods classification between heterogeneous classification |
| CN110287329A (en) * | 2019-07-04 | 2019-09-27 | 刘凡 | A kind of electric business classification attribute excavation method based on commodity text classification |
| CN111126442A (en) * | 2019-11-26 | 2020-05-08 | 北京京邦达贸易有限公司 | Method for generating key attribute of article, method and device for classifying article |
| CN111563529A (en) * | 2020-03-31 | 2020-08-21 | 中国科学院信息工程研究所 | Data category attribute representation method and access control method |
| CN112463971A (en) * | 2020-09-15 | 2021-03-09 | 杭州商情智能有限公司 | E-commerce commodity classification method and system based on hierarchical combination model |
| CN112801720A (en) * | 2021-04-12 | 2021-05-14 | 连连（杭州）信息技术有限公司 | Method and device for generating shop category identification model and identifying shop category |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4004619B2 (en) * | 1998-01-08 | 2007-11-07 | 富士通株式会社 | Inventory management device capable of automatic inventory allocation |
| CN102236663B (en) * | 2010-04-30 | 2014-04-09 | 阿里巴巴集团控股有限公司 | Query method, query system and query device based on vertical search |
-
2021
- 2021-07-23 CN CN202110833914.6A patent/CN113570428B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5179643A (en) * | 1988-12-23 | 1993-01-12 | Hitachi, Ltd. | Method of multi-dimensional analysis and display for a large volume of record information items and a system therefor |
| JP2005208709A (en) * | 2004-01-20 | 2005-08-04 | Fuji Xerox Co Ltd | Data classification processing apparatus, data classification processing method and computer program |
| CN102915498A (en) * | 2011-08-03 | 2013-02-06 | 腾讯科技（深圳）有限公司 | Method and device for goods classification of e-commerce platform |
| CN103593763A (en) * | 2012-08-13 | 2014-02-19 | 腾讯科技（深圳）有限公司 | An information organization method and an apparatus thereof and an information display method and an apparatus thereof |
| CN102841946A (en) * | 2012-08-24 | 2012-12-26 | 北京国政通科技有限公司 | Commodity data retrieval sequencing and commodity recommendation method and system |
| CN103914492A (en) * | 2013-01-09 | 2014-07-09 | 阿里巴巴集团控股有限公司 | Method for query term fusion, method for commodity information publish and method and system for searching |
| CN103778214A (en) * | 2014-01-16 | 2014-05-07 | 北京理工大学 | Commodity property clustering method based on user comments |
| CN103995905A (en) * | 2014-06-13 | 2014-08-20 | 重庆大学 | Electronic commerce content multi-dimensional classification, navigation and skipping method |
| KR20180123826A (en) * | 2017-05-10 | 2018-11-20 | 네모커머스(주) | Correspondences generation system of goods classification between heterogeneous classification |
| CN107730343A (en) * | 2017-09-15 | 2018-02-23 | 广州唯品会研究院有限公司 | A kind of user's merchandise news method for pushing and equipment based on picture attribute extraction |
| CN110287329A (en) * | 2019-07-04 | 2019-09-27 | 刘凡 | A kind of electric business classification attribute excavation method based on commodity text classification |
| CN111126442A (en) * | 2019-11-26 | 2020-05-08 | 北京京邦达贸易有限公司 | Method for generating key attribute of article, method and device for classifying article |
| CN111563529A (en) * | 2020-03-31 | 2020-08-21 | 中国科学院信息工程研究所 | Data category attribute representation method and access control method |
| CN112463971A (en) * | 2020-09-15 | 2021-03-09 | 杭州商情智能有限公司 | E-commerce commodity classification method and system based on hierarchical combination model |
| CN112801720A (en) * | 2021-04-12 | 2021-05-14 | 连连（杭州）信息技术有限公司 | Method and device for generating shop category identification model and identifying shop category |
Non-Patent Citations (5)
| Title |
|---|
| 一种改进的基于商品分类信息的多层关联规则挖掘算法;鲁增秋;陈玉哲;王殿升;;科技情报开发与经济(第14期);全文 * |
| 决策树分类方法研究;魏晓云;;计算机系统应用(第09期);全文 * |
| 利用数据挖掘实现管理客户关系中的客户分类;张莉;牟敏;;商场现代化(第19期);全文 * |
| 基于前缀编码的先根遍历树生成算法的研究与应用;况立群;熊风光;韩燮;;计算机应用与软件(第04期);全文 * |
| 基于商品分类信息的关联规则聚类;阮备军, 朱扬勇;计算机研究与发展(第02期);全文 * |
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