CN106408378A - Price comparison and shopping method applied to electronic commerce - Google Patents
Price comparison and shopping method applied to electronic commerce Download PDFInfo
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- CN106408378A CN106408378A CN201610804319.9A CN201610804319A CN106408378A CN 106408378 A CN106408378 A CN 106408378A CN 201610804319 A CN201610804319 A CN 201610804319A CN 106408378 A CN106408378 A CN 106408378A
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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]
- G06Q30/0623—Item investigation
- G06Q30/0625—Directed, with specific intent or strategy
- G06Q30/0629—Directed, with specific intent or strategy for generating comparisons
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Abstract
The invention provides a price comparison and shopping method applied to electronic commerce. The method includes the following steps that: step S1, the purchase information of a user is picked up; step S2, a model is established, a big data processing platform establishes a purchase training model according to the commodity characteristic information of commodity selling pages which are clicked by a user and corresponding relations between the commodity characteristic information of the clicked commodity selling pages; step S3, commodities are matched; step S4, comparison is carried out again; step S5, identical commodity prices are extracted; and step S6, prices are sorted, identical products of which the prices are lower than the prices of the commodities on the clicked commodity selling pages are extracted through the big data processing platform, and the products are sorted according to the prices and are displayed. With the method adopted, commodity prices required by the user can be extracted from web portals, and are sorted, and therefore, time can be saved. The method has the advantages of multi-angle parity comparison, convenience, high practicability, high efficiency, good user experience and the like.
Description
Technical field
The present invention is a kind of method of rate of exchange shopping in ecommerce, belongs to technical field of mechanical equipment.
Background technology
With scientific and technical continuous development, the species of electronic product also gets more and more, and people have also enjoyed science and technology and sent out
Open up the various facilities brought.People can pass through various types of mobile terminals now, enjoys with relaxing that development in science and technology brings
Suitable life.For example, the mobile terminal such as smart mobile phone, panel computer has become as an important ingredient in people's life,
User can be listened music, play game, shopping at network etc. using mobile terminals such as smart mobile phone, panel computers, give people to carry
Carry out great convenience.
Nowadays, the rate of exchange shopping in shopping at network is risen, and user is being browsed in a certain merchant web site by mobile terminal
The information of a certain commodity when, can show that the merchandise sales page of identical goods in multiple merchant web site (includes every simultaneously
Individual businessman sells the price of identical goods), user can be contrasted, and buys commodity the most inexpensive.
But various Electronic Commerce Gateway Website's are uneven, and price is also mutually variant, with the businessman of commonsense method extraction
The merchandise sales price of the identical goods on website, mostly entirely it is impossible to provide the user with the exhibition of a rate of exchange shopping completing
Show.
Content of the invention
In view of the shortcomings of the prior art, it is an object of the present invention to provide in a kind of ecommerce the rate of exchange shopping method,
To solve the problems, such as to propose in above-mentioned background technology.
To achieve these goals, the present invention is to realize by the following technical solutions：The rate of exchange in a kind of ecommerce
The method of shopping, comprises the following steps：
Step S1, the purchase information of pickup user, shopping at network server is according to the merchandise sales of the clicked on shopping at network of user
Page request, extracts the product features information of the clicked on merchandise sales page, submits to big data processing platform；
Step S2, sets up model, big data processing platform according to the product features information of user's clicked on merchandise sales page, with
And the corresponding relation between the product features information of the clicked on merchandise sales page, set up a purchase training pattern；
Step S3, mates commodity, in big data processing platform, according to model training sample, set up commodity and training pattern it
Between regression model, pre-enter as goods model, extract goods model basic key word, different shoppings at network put down
On platform, carried out using the product features information of the set basic key word rule merchandise sales page clicked on to user
Joining, it is determined whether the match is successful, if it is, extracting the identical goods on different shopping at network platforms, this identical goods being believed
Breath, as important information, extracts this identical goods characteristic information, and carries out next step, if not, using set key word
The product features information of derived sequence merchandise sales clicked on to the user page is mated, the identical business that mating structure is met
Product extract, and simultaneously using this identical goods information as general information, extract this identical goods characteristic information, and carry out next step.
Step S4, contrasts again, by by identical goods characteristic information and, commodity of user's clicked on merchandise sales page
Characteristic information is contrasted, and confirms this identical goods whether by the commodity of user's clicked on merchandise sales page, if it is, carrying out
Next step, if not, carry out step S3.
Step S5, extracts identical goods price, in big data processing platform, by the price tag by identical goods
Numeral as commodity price, it is right that the price of clicked on user for this pricing information merchandise sales page commodity is carried out
Ratio judges whether the price of identical goods is more than the price of user's clicked on merchandise sales page commodity, if it is greater, then deleting
The information of this identical goods, if being less than, carries out next step.
Step S6, price sorts, and will be less than user's clicked on merchandise sales page commodity by big data processing platform
The like products of price propose, and are ranked up according to the height of price and show.
Further, in step sl, the characteristic information of described commodity includes:
Classification residing for commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of commodity, identifies the numeral in this price tag as the price of commodity by shopping at network server；
By shopping at network server, the identification code of commodity, identifies that businessman is attached to the definite attribute on commodity.
Further, in the classification residing in commodity, the multistratum classification of commodity refers to, businessman is for being attached on commodity
Classification information, such as one food commodity, the classification information that businessman is attached on this kind of commodity is the taste of food, the product of food
Board, the effect of the species of food, the productive life of food and food.
Further, in step s3, identical goods characteristic information refers to：
Classification residing for this commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of this commodity, identifies the numeral in this price tag as the valency of commodity by shopping at network server
Lattice；
By shopping at network server, the identification code of this commodity, identifies that businessman is attached to the definite attribute on commodity.
Further, in step s 6, by big data processing platform, it is ranked up according to the height of commodity price, with
When corresponding for commodity link is shown.
Beneficial effects of the present invention：In a kind of ecommerce of the present invention, the method for rate of exchange shopping, is processed by big data
Platform extracts to the feature of commodity, and to carry out the feature of this commodity and the commodity on different shopping at network platforms right simultaneously
Than, further according to the result of contrast, extract the price of identical goods, be ranked up according to the height of price and show, permissible
The commodity price that user is needed is extracted from each portal website, and is ranked up, and has saved the time, has multi-angle ratio
Valency, the advantages of convenient and practical, efficiency high, Consumer's Experience are good.
Specific embodiment
Technological means, creation characteristic, reached purpose and effect for making the present invention realize are easy to understand, with reference to
Specific embodiment, is expanded on further the present invention.
The present invention provides a kind of technical scheme：In a kind of ecommerce, the method for rate of exchange shopping, comprises the following steps：
Step S1, the purchase information of pickup user, shopping at network server is according to the merchandise sales of the clicked on shopping at network of user
Page request, extracts the product features information of the clicked on merchandise sales page, submits to big data processing platform；
Step S2, sets up model, big data processing platform according to the product features information of user's clicked on merchandise sales page, with
And the corresponding relation between the product features information of the clicked on merchandise sales page, set up a purchase training pattern；
Step S3, mates commodity, in big data processing platform, according to model training sample, set up commodity and training pattern it
Between regression model, pre-enter as goods model, extract goods model basic key word, different shoppings at network put down
On platform, carried out using the product features information of the set basic key word rule merchandise sales page clicked on to user
Joining, it is determined whether the match is successful, if it is, extracting the identical goods on different shopping at network platforms, this identical goods being believed
Breath, as important information, extracts this identical goods characteristic information, and carries out next step, if not, using set key word
The product features information of derived sequence merchandise sales clicked on to the user page is mated, the identical business that mating structure is met
Product extract, and simultaneously using this identical goods information as general information, extract this identical goods characteristic information, and carry out next step.
Step S4, contrasts again, by by identical goods characteristic information and, commodity of user's clicked on merchandise sales page
Characteristic information is contrasted, and confirms this identical goods whether by the commodity of user's clicked on merchandise sales page, if it is, carrying out
Next step, if not, carry out step S3.
Step S5, extracts identical goods price, in big data processing platform, by the price tag by identical goods
Numeral as commodity price, it is right that the price of clicked on user for this pricing information merchandise sales page commodity is carried out
Ratio judges whether the price of identical goods is more than the price of user's clicked on merchandise sales page commodity, if it is greater, then deleting
The information of this identical goods, if being less than, carries out next step.
Step S6, price sorts, and will be less than user's clicked on merchandise sales page commodity by big data processing platform
The like products of price propose, and are ranked up according to the height of price and show.
In step sl, the characteristic information of described commodity includes:
Classification residing for commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of commodity, identifies the numeral in this price tag as the price of commodity by shopping at network server；
By shopping at network server, the identification code of commodity, identifies that businessman is attached to the definite attribute on commodity.
In classification residing in commodity, the multistratum classification of commodity refers to, businessman for the classification information being attached on commodity,
Such as one food commodity, businessman is attached to taste that classification information on this kind of commodity is food, the brand of food, food
The effect of species, the productive life of food and food.
In step s3, identical goods characteristic information refers to：
Classification residing for this commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of this commodity, identifies the numeral in this price tag as the valency of commodity by shopping at network server
Lattice；
By shopping at network server, the identification code of this commodity, identifies that businessman is attached to the definite attribute on commodity.
In step s 6, by big data processing platform, it is ranked up according to the height of commodity price, simultaneously by commodity pair
The link answered shows.
As one embodiment of the present of invention：By big data processing platform, the feature of commodity is extracted, will simultaneously
The feature of this commodity is contrasted from the commodity on different shopping at network platforms, further according to the result of contrast, extracts identical business
The price of product, is ranked up according to the height of price and shows, and the commodity price that can need user is from each door
Extract in website, and be ranked up, saved the time, there are the multi-angle rate of exchange, convenient and practical, efficiency high, Consumer's Experience are good etc.
Advantage.
Ultimate principle and principal character and the advantages of the present invention of the present invention have been shown and described above, for this area skill
It is clear that the invention is not restricted to the details of above-mentioned one exemplary embodiment for art personnel, and in the spirit without departing substantially from the present invention or
In the case of basic feature, the present invention can be realized in other specific forms.Therefore, no matter from the point of view of which point, all should be by
Embodiment regards exemplary as, and is nonrestrictive, the scope of the present invention by claims rather than on state
Bright restriction, it is intended that all changes in the implication and scope of the equivalency of claim that fall are included in the present invention
Interior.Any labelling in claim should not be considered as limiting involved claim.
Moreover, it will be appreciated that although this specification is been described by according to embodiment, not each embodiment only wraps
Containing an independent technical scheme, only for clarity, those skilled in the art should for this narrating mode of description
Using description as an entirety, the technical scheme in each embodiment can also form those skilled in the art through appropriately combined
Understandable other embodiment.
Claims (5)
1. in a kind of ecommerce the rate of exchange shopping method it is characterised in that：Comprise the following steps：
Step S1, the purchase information of pickup user, shopping at network server is according to the merchandise sales of the clicked on shopping at network of user
Page request, extracts the product features information of the clicked on merchandise sales page, submits to big data processing platform；
Step S2, sets up model, big data processing platform according to the product features information of user's clicked on merchandise sales page, with
And the corresponding relation between the product features information of the clicked on merchandise sales page, set up a purchase training pattern；
Step S3, mates commodity, in big data processing platform, according to model training sample, set up commodity and training pattern it
Between regression model, pre-enter as goods model, extract goods model basic key word, different shoppings at network put down
On platform, carried out using the product features information of the set basic key word rule merchandise sales page clicked on to user
Joining, it is determined whether the match is successful, if it is, extracting the identical goods on different shopping at network platforms, this identical goods being believed
Breath, as important information, extracts this identical goods characteristic information, and carries out next step, if not, using set key word
The product features information of derived sequence merchandise sales clicked on to the user page is mated, the identical business that mating structure is met
Product extract, and simultaneously using this identical goods information as general information, extract this identical goods characteristic information, and carry out next step；
Step S4, contrasts again, by by identical goods characteristic information and, product features of user's clicked on merchandise sales page
Information is contrasted, and confirms this identical goods whether by the commodity of user's clicked on merchandise sales page, if it is, carrying out next
Step, if not, carry out step S3；
Step S5, extracts identical goods price, in big data processing platform, by the number in the price tag by identical goods
Word, as the price of commodity, the price of clicked on user for this pricing information merchandise sales page commodity is contrasted, is sentenced
Whether the price of disconnected identical goods is more than the price of user's clicked on merchandise sales page commodity, if it is greater, then deleting this phase
With the information of commodity, if being less than, carry out next step；
Step S6, price sorts, and will be less than the price of user's clicked on merchandise sales page commodity by big data processing platform
Like products propose, be ranked up according to the height of price and show.
2. in a kind of ecommerce according to claim 1 the rate of exchange shopping method it is characterised in that：In step sl,
The characteristic information of described commodity includes：
Classification residing for commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of commodity, identifies the numeral in this price tag as the price of commodity by shopping at network server；
By shopping at network server, the identification code of commodity, identifies that businessman is attached to the definite attribute on commodity.
3. in a kind of ecommerce according to claim 2 the rate of exchange shopping method it is characterised in that：Residing for commodity
In classification, the multistratum classification of commodity refers to, businessman is for the classification information being attached on commodity, such as one food commodity, business
Family is attached to the taste that classification information on this kind of commodity is food, the brand of food, the species of food, the productive life of food
And the effect of food.
4. in a kind of ecommerce according to claim 1 the rate of exchange shopping method it is characterised in that：In step s3,
Identical goods characteristic information refers to：
Classification residing for this commodity, extracts the multistratum classification of commodity by shopping at network server；
The price tag of this commodity, identifies the numeral in this price tag as the valency of commodity by shopping at network server
Lattice；
By shopping at network server, the identification code of this commodity, identifies that businessman is attached to the definite attribute on commodity.
5. in a kind of ecommerce according to claim 1 the rate of exchange shopping method it is characterised in that：In step s 6,
By big data processing platform, it is ranked up according to the height of commodity price, corresponding for commodity link is shown simultaneously.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610804319.9A CN106408378A (en) | 2016-09-02 | 2016-09-02 | Price comparison and shopping method applied to electronic commerce |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201610804319.9A CN106408378A (en) | 2016-09-02 | 2016-09-02 | Price comparison and shopping method applied to electronic commerce |
Publications (1)
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| CN106408378A true CN106408378A (en) | 2017-02-15 |
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| CN201610804319.9A Pending CN106408378A (en) | 2016-09-02 | 2016-09-02 | Price comparison and shopping method applied to electronic commerce |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107256509A (en) * | 2017-05-27 | 2017-10-17 | 北京小米移动软件有限公司 | Price comparing method and device, terminal, server and storage medium |
| CN107346334A (en) * | 2017-06-27 | 2017-11-14 | 珠海市魅族科技有限公司 | Information search method and device, computer installation and computer-readable recording medium |
| CN108446958A (en) * | 2018-03-20 | 2018-08-24 | 慈而宽电子商务（上海）有限公司 | Information processing method and system |
| CN108596743A (en) * | 2018-05-10 | 2018-09-28 | 北京三快在线科技有限公司 | Merchandise information processing method, device, storage medium and computer equipment |
| CN109923870A (en) * | 2017-03-24 | 2019-06-21 | 朴洙范 | By the real-time shopping method of the video identification in broadcast and the smart machine of the application program for realizing it is installed |
| CN110298699A (en) * | 2019-06-27 | 2019-10-01 | 北京创鑫旅程网络技术有限公司 | OTA house type Pricing Program processing method and processing device |
| CN110335071A (en) * | 2019-06-21 | 2019-10-15 | 上海媒科锐奇网络科技有限公司 | Networked shopping system |
| CN110503525A (en) * | 2019-08-26 | 2019-11-26 | 太仓红码软件技术有限公司 | Intelligent consumption guard method and its system based on big data and shopping at network |
| CN111353847A (en) * | 2020-02-11 | 2020-06-30 | 北京加立技术有限公司 | Multi-platform multi-dimensional price comparison method and device |
| CN111461840A (en) * | 2020-04-05 | 2020-07-28 | 十堰时风达工贸有限公司 | Cross-border e-commerce big data intelligent processing and transmission method and platform based on block chain |
| CN112184361A (en) * | 2020-09-02 | 2021-01-05 | 珠海格力电器股份有限公司 | Method and device for displaying commodity information in shopping cart in e-commerce shopping platform |
| CN112533343A (en) * | 2020-12-23 | 2021-03-19 | 重庆化工职业学院 | City street lamp intelligent monitoring system under thing networking mode |
| CN112884072A (en) * | 2021-03-22 | 2021-06-01 | 南京奥派信息产业股份公司 | Commodity data classification processing and comparison technical method and system |
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Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109923870A (en) * | 2017-03-24 | 2019-06-21 | 朴洙范 | By the real-time shopping method of the video identification in broadcast and the smart machine of the application program for realizing it is installed |
| CN107256509A (en) * | 2017-05-27 | 2017-10-17 | 北京小米移动软件有限公司 | Price comparing method and device, terminal, server and storage medium |
| CN107346334A (en) * | 2017-06-27 | 2017-11-14 | 珠海市魅族科技有限公司 | Information search method and device, computer installation and computer-readable recording medium |
| CN108446958A (en) * | 2018-03-20 | 2018-08-24 | 慈而宽电子商务（上海）有限公司 | Information processing method and system |
| CN108596743A (en) * | 2018-05-10 | 2018-09-28 | 北京三快在线科技有限公司 | Merchandise information processing method, device, storage medium and computer equipment |
| CN110335071A (en) * | 2019-06-21 | 2019-10-15 | 上海媒科锐奇网络科技有限公司 | Networked shopping system |
| CN110298699A (en) * | 2019-06-27 | 2019-10-01 | 北京创鑫旅程网络技术有限公司 | OTA house type Pricing Program processing method and processing device |
| CN110503525A (en) * | 2019-08-26 | 2019-11-26 | 太仓红码软件技术有限公司 | Intelligent consumption guard method and its system based on big data and shopping at network |
| CN110503525B (en) * | 2019-08-26 | 2021-09-28 | 上海臻客信息技术服务有限公司 | Intelligent consumption protection method and system based on big data and online shopping |
| CN111353847A (en) * | 2020-02-11 | 2020-06-30 | 北京加立技术有限公司 | Multi-platform multi-dimensional price comparison method and device |
| CN111461840A (en) * | 2020-04-05 | 2020-07-28 | 十堰时风达工贸有限公司 | Cross-border e-commerce big data intelligent processing and transmission method and platform based on block chain |
| CN112184361A (en) * | 2020-09-02 | 2021-01-05 | 珠海格力电器股份有限公司 | Method and device for displaying commodity information in shopping cart in e-commerce shopping platform |
| CN112533343A (en) * | 2020-12-23 | 2021-03-19 | 重庆化工职业学院 | City street lamp intelligent monitoring system under thing networking mode |
| CN112533343B (en) * | 2020-12-23 | 2023-02-03 | 重庆化工职业学院 | City street lamp intelligent monitoring system under thing networking mode |
| CN112884072A (en) * | 2021-03-22 | 2021-06-01 | 南京奥派信息产业股份公司 | Commodity data classification processing and comparison technical method and system |
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Application publication date: 20170215 |
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