WO2012146136A1 - Procédé et système de recherche d'informations - Google Patents

Procédé et système de recherche d'informations Download PDF

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Publication number
WO2012146136A1
WO2012146136A1 PCT/CN2012/074093 CN2012074093W WO2012146136A1 WO 2012146136 A1 WO2012146136 A1 WO 2012146136A1 CN 2012074093 W CN2012074093 W CN 2012074093W WO 2012146136 A1 WO2012146136 A1 WO 2012146136A1
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WO
WIPO (PCT)
Prior art keywords
information
commodity
product
search
clustering
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PCT/CN2012/074093
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English (en)
Chinese (zh)
Inventor
闫鹏
李彦宏
蔡虎
沈毅
李磊
Original Assignee
北京百度网讯科技有限公司
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Publication of WO2012146136A1 publication Critical patent/WO2012146136A1/fr

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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
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques

Definitions

  • the invention relates to an information search method and system, in particular to a search method and system capable of clustering according to similarity in a search process.
  • online shopping through the Internet has become an important way of shopping.
  • the advantages of online shopping mainly include: convenience, as long as there is an Internet, you can shop anywhere, anytime; Wide range, you can browse and compare the same kind or different kinds of goods sold by many different merchants at the same time; the price is cheap, and there is a big discount on the price of the goods sold in the physical store. Based on these advantages of online shopping, an online shopping platform that provides online shopping has been fully developed.
  • an input box of the product search interface is provided, and when the user enters the product query condition in the search interface, the corresponding product search result is quickly obtained, and the search results of the products can be sorted according to different attributes, so that The user can quickly find the item that he most desires to search.
  • the sorting attributes include: sorting according to the sales volume of the goods, sorting according to the geographical position of the sellers of the goods, sorting according to the reputation of the sellers of the goods, sorting according to the price of the goods, and the like.
  • the method of sorting these items helps the user to quickly find the item that he or she desires to purchase.
  • the product search results are many, the above product sorting methods still cannot fully satisfy the user's needs.
  • a common problem is that in the existing product search, after searching for the product according to the product query keyword submitted by the user, the query result is directly listed for use by the user, and many of the product search results are the same product, only These sellers who provide these items differ in that the same or similar items are not clustered for use by the user, requiring the user to perform multiple screenings or searches before locating the items that they really desire.
  • the keyword searched by the user is “Nokia mobile phone” (corresponding to the area “A” in FIG.
  • An object of the present invention is to provide an improved product search method for clustering according to the similarity of products in a product search in order to solve the above-mentioned prior art defects, and the product search method can be the same in the product search result. Or similar product clusters are combined to show.
  • Another object of the present invention is to provide an improved merchandise search system for clustering according to the similarity of merchandise in merchandise search in order to solve the above-mentioned prior art defects, and the merchandise search system can apply the improved A product search method for clustering according to the similarity of products in product search.
  • the commodity search method of an embodiment of the present invention includes the following steps:
  • the article search system of one embodiment of the present invention includes:
  • a clustering module configured to pre-index the product information in the product information database to obtain commodity index information; extract the product image according to the commodity index information, and extract the product image feature value, which is similar to the feature value
  • the commodities are clustered to obtain at least one commodity clustering information
  • a UI module configured to receive a user search request
  • a search module configured to search the commodity index information and the commodity clustering information related to the search request, to obtain a search result.
  • the invention has the beneficial effects of improving the method and system for searching commodities, increasing the ranking module of the products, optimizing the sorting result of the search, clustering the same or similar products, increasing the regularity of the product list, and reducing the user's Further screening operations, improve search efficiency, and save network traffic; at the same time, reduce the number of times the client initiates access requests to the server, thereby reducing the processing pressure of the server, reducing the occupied network bandwidth, improving the network transmission speed, and avoiding the network. Blocked.
  • Figure 1 is a schematic diagram of the results of a product inquiry of an existing online shopping website.
  • FIG. 2 is a schematic diagram showing the working principle of the product search system of the present invention interacting with a client.
  • Fig. 3 is a block diagram showing the structure of a commodity search system according to an embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of the clustering module in FIG. 3.
  • Fig. 5 is a flow chart showing the workflow of the product search method according to an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of a web page in which product query results generated by applying the product search method of the present invention are combined according to clusters.
  • FIG. 7 is a schematic diagram of a product query result webpage after the product clustering in FIG. 6 is expanded.
  • the client 20 includes a browser, the client can open the search engine through the browser, and input the query condition in the search engine.
  • the input query condition is text information, of course, the query condition. It may also be picture information, video information, etc., of course, in the preferred embodiment of the invention, the search engine is the item search system of the present invention.
  • the commodity search system 10 receives the query condition input by the customer into the browser through the network, and after searching the query condition, returns the search result to the browser.
  • the commodity search system 10 may include one or more servers, and the client 20 may include one or more user terminal devices such as a personal computer, a notebook computer, a wireless telephone, a personal digital processing (PDA), or other computer.
  • PDA personal digital processing
  • the servers and terminal devices are architecturally comprised of basic components such as buses, processing systems, storage systems, one or more input/output systems, and communication interfaces.
  • the bus may include one or more wires for communication between the various components of the server or terminal device.
  • a processing system includes various types of processors or microprocessors for executing instructions, processing processes, or threads.
  • the storage system may include a dynamic memory such as a random access memory (RAM) that stores dynamic information, and a static memory such as a read only memory (ROM) that stores static information, and a large-capacity memory including a magnetic or optical recording medium and a corresponding drive.
  • the input system allows the user to input information to a server or terminal device such as a keyboard, mouse, stylus, voice recognition system, or biometric system.
  • the output system includes a display, a printer, a speaker, and the like for outputting information.
  • Communication interfaces are used to enable a server or terminal device to communicate with other systems or systems.
  • the communication interfaces can be connected to the network through a wired connection, a wireless connection, or an optical connection, so that the commodity search system 10 and the client 20 can communicate with each other through the network.
  • the network may include a local area network (LAN), a wide area network (WAN), a telephone network such as the Public Switched Telephone Network (PSTN), an intranet of the enterprise, the Internet, or a combination of these.
  • a product search system includes a web service module 100, a UI module 102 in interactive communication with the web service module 100, a search module 104 in interactive communication with the UI module, and the The clustering module 106 communicated by the search module 104, the data storage module 108 in communication with the clustering module 106, and the update module 109 in communication with the data storage module 108. It is worth mentioning that these modules can be stored and run on the same server, and can be stored and run on multiple servers.
  • the web service module 100 is configured to receive the query condition sent from the client 20 through a network protocol, and transfer the query condition to the UI module 102. In addition, the web service module 100 is further configured to receive the UI module 102 to return. The result page and return the result page to client 20.
  • the UI module 102 is configured to receive the query condition sent by the web service module 100, and send the query condition to the search module 104. In addition, the UI module 102 is further configured to receive the return by the search module 104. After the search results are assembled and the search results are assembled into a result page, the result page is returned to the web service module 100.
  • the search module 104 is configured to search for commodity index information and commodity clustering information related to the search request, and obtain a search result. Specifically, the search module 104 receives the query condition input by the UI module 102, and queries the clustering module 106 according to the query condition to obtain a search including at least one commodity index information and commodity clustering information. result. Preferably, in the preferred embodiment of the present invention, the search module 104 is further configured to search for clustered commodity average price information according to the clustering situation in the clustering module 106, and send the result to the UI. Module 102.
  • the clustering module 106 is configured to establish and store commodity index information and commodity clustering information. In the preferred embodiment of the present invention, the clustering module 106 is further configured to establish and store commodity average price information. How to obtain the commodity index information, the commodity clustering information, and the commodity average price information can be referred to the following detailed description in conjunction with FIG. 5.
  • the data storage module 108 is configured to establish a commodity information database. Specifically, the data storage module 108 stores a large amount of product information submitted by the seller, and the product information used in the present invention is mainly a product name and a picture of the product. Of course, preferably, the item information in the data storage module 108 further includes a commodity price, a category, a name, a summary, and the like.
  • the update module 109 is configured to periodically update the commodity index information and the commodity clustering information according to the update information of the product information database.
  • the update module 109 is further configured to periodically update the commodity average price information.
  • the clustering module 106 includes an indexing unit 1060, a clustering unit 1062, a price calculating unit 1064, and a storage unit 1066.
  • the indexing unit 1060 is configured to perform indexing according to the product name in the commodity information database to obtain commodity index information.
  • the index not only indexes all the commodity information stored in the data storage module 108, but also divides the index into a plurality of corresponding categories according to the commodity attribute, for example, if the product is The attribute is indexed by the brand, and the brand name is retrieved in all the product names.
  • the brand name includes "Nokia" into one category and the corresponding index is established, and the product name including "Motorola" is classified into another category.
  • the product attribute can also be other, such as variety, sales area, sales price, seller credit, etc., according to the above goods
  • the attribute is a similar way for the brand to create a complete index table for all items stored in the data storage module 108.
  • the clustering unit 1062 is configured to extract a product image according to the commodity index information, extract the commodity image feature value, and cluster the commodities close to the feature value to obtain at least one commodity clustering information.
  • the picture of the item refers to at least one picture information indicating the feature of the item included in the item information of all items stored in the data storage module 108.
  • the characteristic value of the commodity is calculated by the SIFT algorithm.
  • the price calculation unit 1064 is configured to calculate the commodity average price information in the at least one commodity clustering information.
  • the price which can be provided to the user as part of the search results, allows the user to have a clearer understanding of the sales of the product, which is conducive to improving the customer experience.
  • the storage unit 1066 is configured to store the commodity index information and the commodity clustering information.
  • the storage unit 1066 is further configured to store commodity average price information, so that the search module 104 can quickly search for the commodity index information, the commodity clustering information, and the commodity clustering information in the storage unit 1066.
  • the product average price information, and the searched results are assembled into a result page through the UI module 102 and transmitted to the user.
  • Fig. 5 is a flow chart showing the workflow of the product search method according to an embodiment of the present invention. The method includes the following steps:
  • the product information database is stored in the data storage module 108 as described in FIG.
  • the product information mainly includes a product name and a picture of the product.
  • the product information may further include a product price, a category, a name, a summary, and the like.
  • the steps of establishing the commodity information database are well known to those skilled in the art and will not be described herein.
  • indexing according to the product name in the product information database to obtain commodity index information preferably, in the preferred embodiment of the present invention, the index can not only index all the commodity information stored in the data storage module 108, but also The index can be divided into multiple corresponding categories according to the product attribute. For example, if the brand is indexed according to the product attribute, all brands with the brand name are retrieved, for example, the item name includes “Nokia” and is classified into a category.
  • the product name contains "Motorola” into another category and corresponding indexing, and so on, you can create a complete index table according to the product attribute brand, of course, the product attribute can also be other Such as the variety, sales area, sales price, seller credit, etc., a complete index table can be established for all the items stored in the data storage module 108 in a similar manner to the above-mentioned product attributes.
  • the step S200 is performed by the indexing unit 1060.
  • step S3 extracting a product image according to the product index information, extracting the product image feature value, and clustering the products having the similar feature values to obtain at least one product clustering information; in an embodiment of the present invention
  • the step S3 is completed by the clustering unit 1062 in FIG. 5, and the clustering unit 1062 is configured to compare the feature values of the pictures of the products under the certain product index classification, and put the products with the similar feature values of the pictures into In a cluster.
  • the picture of the item refers to at least one picture information indicating the feature of the item included in the item information of all items stored in the data storage module 108.
  • the characteristic value of the commodity is calculated by the SIFT algorithm.
  • the main steps include: 1. Detecting scale space extreme points; 2. Precisely locate extreme points; 3. Specify direction parameters for each key point; 4. Key point descriptor generation.
  • a detailed description of the SIFT algorithm can be found in the publicly available materials, and will not be described in detail herein.
  • the clustering module 106 periodically reads the change of the commodity information database in the data storage module 108 and updates it to the index cluster storage module, that is, periodically according to the update information of the commodity information database in the data storage module 108. And updating the commodity index information and the commodity clustering information.
  • the user search request is received.
  • the search request is a product query condition input by the user in the client browsing, and the keyword is transmitted to the search module 104 through the web service module 100 and the UI module 102.
  • step S6 Search for the commodity index information and the commodity clustering information related to the search request to obtain a search result.
  • this step there is also search for commodity average price information associated with the search request.
  • the step S2 is accomplished by the search module 104 of FIG.
  • the searching unit 1030 is configured to receive the query condition input by the UI module 102, and query the query condition in the clustering module 106 to obtain at least one type of commodity after clustering, and corresponding to the commodity. The average price of the goods.
  • the search result is assembled into a result page by the UI module 102, and then sent to the user client through the Web service module 100.
  • a step (not shown) is further included: calculating the average price information of the commodity in the at least one commodity clustering information.
  • the step is performed by a price calculation unit 1064 for calculating an average price of the items in the one cluster.
  • a price calculation unit 1064 for calculating an average price of the items in the one cluster.
  • the storing the commodity average price information is further included.
  • the clustering module 106 periodically reads the change of the commodity information database in the data storage module 108 and updates it to the index cluster storage module, that is, periodically updates the location according to the update information of the commodity information database in the data storage module 108.
  • Product index information, product clustering information, and commodity average price information are further included.
  • step S6 further comprising searching for the commodity average price information related to the search request.
  • the query condition "Nokia” is entered in the query window of the product search engine (the area marked “C” in FIG. 6) opened in the client browser.
  • the obtained cluster query result is assembled into the result page through the UI module 102, and then sent back to the client browser by the Web service module, as shown in FIG. 6 as “D1” and “D2”.
  • the areas of "D3" respectively show the clustering results of three models of Nokia mobile phones.
  • the clustering results include the name, profile, and picture of the product, as well as the average price of the product, as well as the product. The number of sales merchants.
  • FIG. 7 is a schematic diagram showing the result of the product query after the "D1" product clustering in FIG. 6 is expanded. It can be seen that after the "D1" product clustering in Fig. 6 is expanded, the models of all the products in the cluster are the same (i.e., the Nokia mobile phone model number 5800), and all the products are only in accordance with the seller's Different (areas labeled "E” in Figure 7) are provided to the user one by one.
  • the commodity search method and system of the present invention improves the method and system for searching for goods, and by clustering modules of products, optimizing the sorting result of the search, clustering the same or similar commodities.
  • Increase the regularity of the product list reduce the user's further screening operations, improve search efficiency, and save network traffic; at the same time, reduce the number of times the client initiates access requests to the server, thereby reducing the processing pressure of the server and reducing the occupied network bandwidth.

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  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

L'invention concerne un procédé et un système de recherche d'informations, ledit procédé comprenant : l'indexage à l'avance conformément à des informations de marchandises dans une base de données d'informations de marchandises et l'obtention d'informations d'index de marchandises; conformément auxdites informations d'index de marchandises, l'extraction d'images de marchandises et l'extraction d'une valeur propre desdites images de marchandises, le groupement des marchandises dont les valeurs propres sont proches de ladite valeur propre, et l'obtention d'au moins un élément des informations de groupe de marchandises; après la réception de demandes de recherche d'utilisateur, la recherche desdites informations d'index de marchandises et desdites informations de groupe de marchandises associées auxdites demandes de recherche, et l'obtention des résultats de recherche. La présente invention groupe les mêmes marchandises ou des marchandises similaires, réduisant par conséquent d'autres opérations de filtrage d'utilisateurs, améliorant l' efficacité de recherche, économisant un trafic de réseau, et diminuant simultanément les temps de demande pour un accès d'un client à un serveur, réduisant la contrainte de traitement du serveur, réduisant la bande passante de réseau occupée, améliorant la vitesse de transmission de réseau, et évitant une congestion de réseau.
PCT/CN2012/074093 2011-04-26 2012-04-16 Procédé et système de recherche d'informations WO2012146136A1 (fr)

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CN104331810A (zh) * 2013-07-22 2015-02-04 腾讯科技（深圳）有限公司 团购信息处理方法、装置及系统
CN111161016A (zh) * 2019-12-09 2020-05-15 广东禧越网络科技有限公司 一种基于地区商家保护政策的厂家直销方法与购物平台
CN111198961A (zh) * 2018-11-16 2020-05-26 北京京东尚科信息技术有限公司 商品搜索方法、装置及服务器
CN115798517A (zh) * 2023-02-08 2023-03-14 南京邮电大学 基于语音信息特征数据的商品搜索方法及系统

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CN103136680A (zh) * 2013-03-13 2013-06-05 江苏乐买到网络科技有限公司 一种呈现近似网络商品的方法
CN104715407A (zh) * 2013-12-17 2015-06-17 青岛龙泰天翔通信科技有限公司 一种智慧社区网络购物装置
CN104376052B (zh) * 2014-11-03 2017-07-14 杭州淘淘搜科技有限公司 一种基于商品图像的同款商品合并方法
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CN111161016A (zh) * 2019-12-09 2020-05-15 广东禧越网络科技有限公司 一种基于地区商家保护政策的厂家直销方法与购物平台
CN115798517A (zh) * 2023-02-08 2023-03-14 南京邮电大学 基于语音信息特征数据的商品搜索方法及系统

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