JP2002063394A - System and method for selling and buying article - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a system and a method for article selling and buying which can speedily retrieve an article having plural specifications that a buyer specifies from a registered database with a high matching degree. SOLUTION: When the buyer specifies desired article information 2a including plural purchase specifications (information) Q1 to Q5, a control means (retrieval means) 10 accesses desired article databases (DB) 22, 60, and 62 stored with desired sold article information 22a having one or more pieces P1 to P4 of sale specification information is stored corresponding to sellers (information) S1, retrieves desired sold article information including at least partially matching sale specification information among the plural pieces Q1 to Q5 of purchase specifications (information) Q1 to Q5 from the desired sold article database (DB) 22, and sends it to buyer terminals 70 and 72.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a merchandise trading system and method, such as an Internet auction, for searching for goods desired by a buyer from seller information registered on a Web site, for example.

[0002]

2. Description of the Related Art In recent years, with the spread of the Internet, so-called net auctions have been actively conducted. Such an online auction is performed by a buyer or a seller registering product information on a Web site called an auction site in advance, and searching for a buyer / seller of a desired product using, for example, a product name as a key. In addition, usually, a search for a trading partner is performed on the system using a relatively small number of keywords such as the above-mentioned product name, price and delivery date, and the search criteria is generally determined based on whether or not there is a corresponding product name. It is a target.

[0003]

However, the above-mentioned net auction has the following problems.
First, the buyer needs to access a predetermined information source (auction site) himself and search for the desired product. Further, since the number of information sources that the buyer knows himself is limited, the search is performed. , And the probability of a search hit is reduced. In the conventional search, if the product name and the product uniquely correspond to each other, a reliable search can be performed. It is necessary to determine whether or not to search for the product desired by the seller. Such a judgment can usually be made only by an experienced person in the product field, and it has been difficult to realize this on an auction site system.

In particular, when a product to be bought and sold has a large number of specifications, it is actually required to search for a product close to the product even if there is no product that satisfies all the specifications desired by the buyer. Since it is difficult for the system to determine which product is a product “close” to the buyer's specifications, such a product could not be used as a target of a conventional online auction.

[0005] The present invention has been made in view of the above-mentioned problems, and allows a buyer to access a variety of information sources without himself accessing a variety of products specified by the buyer from a registered database. It is an object of the present invention to provide a merchandise trading system and method capable of quickly searching with a high degree of matching.

[0006]

In order to achieve the above-mentioned object, a merchandise trading system according to the present invention is designed so that, when a buyer designates desired merchandise information including a plurality of pieces of purchase specification information, one or more sales specifications are provided. The desired product information having the information accesses the desired product database stored in correspondence with the seller information, and the desired product information including the sales specification information that at least partially matches the plurality of purchase specification information, It is characterized by comprising a search means for searching from the sales desired product database.

[0007] In the merchandise trading system, it is preferable that the merchandise trading system further includes transmitting means for transmitting the desired merchandise information searched by the search means to the buyer terminal.
It is preferable that the merchandise trading system further includes the desired merchandise database.

Further, in the commodity trading system of the present invention, the purchase specification information is ranked, and numerical information corresponding to the ranking or the degree of coincidence between the purchase specification information and the sales specification information is stored. Further comprising a search information database, wherein, when the predetermined sales specification information matches the respective purchase specification information, the search means compares the purchase specification information with the predetermined sales specification information based on the search information database. By characterizing the degree of coincidence, it is possible to search for desired product information that most satisfies the purchase conditions of the buyer in the previous term.

In the merchandise trading system, the merchandise trading system further includes an evaluation database for storing evaluation information of the buyer with respect to the merchandise or seller with which the transaction has been made, and the search means may refer to the evaluation information in a subsequent search. preferable. In the merchandise trading system, it is preferable that the merchandise trading system further includes a search result database that stores search results of the search unit regarding the merchandise for which a transaction has been established, and that the search unit refers to the search results in subsequent searches.

In the merchandise trading system, a plurality of search means are provided, and each search means has a different search criterion. When the buyer designates the purchase desired merchandise information, any of the search means is used for the search. It is preferable to be able to specify whether

In the merchandise trading system, if the number of desired products satisfying the purchase condition of the buyer in the previous term does not reach the purchase number of the buyer, the purchase condition and the shortage of the buyer in the previous term are notified and the seller is notified. It is preferable to further include a notification means for recruiting.

[0012] In the method of selling and selling commodities of the present invention, when a buyer designates the desired commodity information, the desired commodity database is accessed and at least a part of the plurality of purchase specification information coincides with the corresponding sales specification information. And a step of retrieving desired product information including the following from the desired product database.

[0013]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to FIG. FIG. 1 is a merchandise trading system (hereinafter, referred to as “this system” as appropriate) 50 of the present invention.
FIG. 1 is a configuration block diagram illustrating one embodiment of the present invention, in which a control means (search means) 10, an input / output control means (transmitting means) 12 for transmitting / receiving information to / from a network 100, and a buyer information database (hereinafter referred to as “DB” as appropriate) 2, an evaluation DB 4, a search result DB 6, and a search information DB 8. In this embodiment, the merchandise information integration DB 20, the desired merchandise DB 22, the purchase input information DB 24, the search means selection information DB 26, the seller recruitment page (notification means) 30
Etc. are further provided. The control means 10 controls the entire system and can be realized as a central processing unit of a predetermined server device (not shown). And the commodity trading system 5
0 constitutes a Web site (auction site) as a whole.

The system 50 is connected to buyer terminals 70 and 72 and seller terminals 80 and 82 via a network 100 such as the Internet. Also, the network 100 has another Web site (information source) 20.
0 and 210 are connected, and each web site stores a desired product DB6 similar to the desired product DB22 of the present system.
A virtual store and an electronic mall storing 0 and 62, respectively. And search means of the system 50
(Control means) The DBs 60 and 62 can be accessed from 10 to obtain predetermined information. Note that, in the present system, it is not essential to have the sales desired product DB22, and the sales desired product DB22 may be provided outside.
In this system, it is sufficient that the system has access information to the external sales-desired product DB 22.

As the network 100, instead of the Internet, a dedicated line, a LAN (Local Area Network) is used.
rk), WAN (Wide Area Network) and the like may be used. Also, buyer terminals 70 and 72, seller terminals 80 and 82
Personal computer, STB (Set Top
Box: home communication terminal), mobile phone, PHS (registered trademark), PDA (Personal Digital A
ssistants: a personal information device) or other portable terminal (owned by user A) can be used. In addition to the above, the mobile terminal may be mobile (mobile) such as a palmtop computer or a laptop computer.
Each mobile terminal is appropriately equipped with a browser capable of browsing Web pages. In this embodiment,
Terminals 72 and 80 are portable terminals, and mobile communication network 110
Is connected to the network 100 via the.

In the system 50, a buyer information DB
Reference numeral 2 stores desired product information (buyer data) 2a including predetermined information (authentication information, name, etc.) regarding the buyer, information (product name, etc.) regarding the desired product to be purchased, purchase specifications (Q1 to Q5), and the like. The buyer data 2a is input to the buyer terminals 70 and 72 by the buyers C1 and C2 who have accessed the system 50.

The sales-desired product DB 22 (60, 62)
Specific information on the seller (authentication information, name, etc.), information on the product desired to be sold (product name, etc.), sales specifications (P1 to P1)
Desired product information (seller data) 22 including P4)
a is stored. Here, if the seller data is described in a special code for classifying goods and services or information of different databases that can be integrated, other Web
This is preferable because the information of the DBs 60 and 62 stored in the site can be integrated and searched. In this case, if the information of the DB 6 and the information of the DBs 60 and 62 of other websites are collectively stored in the product information integration DB 22 as appropriate, the search of the control unit (search unit) 10 is improved. As a language, for example, HTML (Hyper Text Markup Langua)
ge) and XML (eXtensive Markup Language).

The evaluation DB 4 stores evaluation data 4a including the name of a traded product, its specifications (P1 to P4), seller information, and buyer evaluation. Here, the evaluation of the buyer may be that relating to the product such as the quality of the product, or that relating to the seller such as after-sales service. The search result DB 6 stores information (product name, purchase specification (Q1 to Q5), sales specification (P1 to P
4) The search data 6a including the buyer's evaluation (matching evaluation) on the degree of matching (matching degree) of the product is stored. The matching evaluation will be described later.

The search information DB 8 stores a search matrix used as a criterion at the time of search, which will be described in detail later, and the purchase input information DB 24 stores a purchase input template used at the time of buyer's purchase input. Search means selection information DB
26 stores the past search results of each search means (e.g., matching degree of seller data with buyer data, evaluation of buyer, etc.) when there are a plurality of search means, and selects any search means when the buyer makes a purchase request. It is a base to determine whether to use. Further, the seller recruiting page 30 publishes the purchase conditions and the missing number on the Web when the number of sellers satisfying the buyer's purchase conditions is insufficient, and recruits sellers who can provide the products.

The above-described desired product information (seller data) and desired product information (buyer data) are shown in detail in FIG. 2 and FIG. In FIG. 2, the seller information 22a includes a seller ID (Identificatio).
n: identification information) 22s, seller name / provider name 22t, seller face information (name, etc.) 22u, desired product information (product name, quantity, sales specifications, etc.) 22v, seller contact means 22w, charge information 1 (Sale price, commission, settlement means, etc.) 22x, fee information 2 (hammer price price (to be described later) when conducting an auction, etc.) 22y, and exchange information link (P1 to Pn, link to predetermined information) 22z. ing. In FIG. 3, the buyer information 2a is
Buyer ID (Identification: identification information) 2s, buyer face information (name, etc.) 2u, desired product information (product name, quantity, purchase specifications, etc.) 2v, contact means 2 to buyer
w, price information 1 (purchase desired price, settlement means, etc.) 2x, price information 2 (purchase designated price when performing an auction (described later)
Etc.) 2y.

Next, referring to FIG. 4, a description will be given of a processing flow of merchandise trading in the present system 50. In FIG. 4, first, the seller inputs information (seller data) relating to a product to be sold from a predetermined seller terminal to the system or a desired-to-sell information DB on another Web site (step 400). The input items may be, for example, those shown in FIG. The control means 10 of the present system appropriately converts the information registered in the sales desire information DB
0 (step 500).

Next, the buyer accesses the system by specifying, for example, a URL (Uniform Resource Locator) from a predetermined buyer terminal and inputs authentication information (step 3).
00). The control unit 10 of the present system performs an authentication process based on a DB (not shown) storing authentication information for each buyer (step 510). Of the purchase input screen (purchase input template) of the buyer terminal 7
0 and 72 display the screen on the display unit of the terminal (step 310). The buyer inputs purchase information (buyer data) of the desired product from the buyer terminal, and selects one of a plurality of search means in a predetermined case (step 32).
0).

The control means 10 of the present system searches the seller data registered in the merchandise information integration DB 20 for suitable information based on the buyer data (step 520). Then, an auction to be described later is appropriately performed on the searched seller data and buyer data, and sellers, buyers, and transaction prices are determined in accordance with the results (step 530). The control means 10 transmits the transaction result, and the buyer terminal and the seller terminal respectively receive the information (steps 330 and 410). Buyer
The payment information is input from the buyer terminal based on the information (step 340), and the control means 10 performs the payment processing based on the information (step 540). Control means 10
Transmits the settlement result, and the buyer terminal and the seller terminal respectively receive the information (steps 350 and 420).
In addition, when the transaction is completed,
When the sales volume of the seller is insufficient, the control means 10 calculates the shortage quantity from the seller data and the buyer data (step 550), and a predetermined notification means (seller recruitment page).
The information on the purchase conditions and the number is posted on the list, and the seller is recruited (step 560). Further, in the case where the transaction is completed, the administrator of the present system may collect a predetermined fee from the buyer and the seller.
Transmits the charging information to the buyer terminal and the seller terminal as appropriate.

Next, a search method performed by the control means (search means) 10 will be described with reference to FIG. FIG.
4 shows an example of a search matrix when a frame relay switch (data exchange device) is used as a product. In this figure, a plurality of specifications of this product (frame relay switch) are listed, and each specification is ranked in any one of ranks A, B, and C.

Here, the specification belonging to the rank A has the highest importance, and the specifications belonging to the rank A of the buyer data must all match the specifications of the seller data.
Here, “both agree” means that the seller data has the specifications of the buyer data and the specific conditions of each specification (for example, the numerical value of “4096 bytes” for “maximum packet length”, the “INS (registered "Trademark) net backup" means "whether possible or not". Then, in order to quantify the degree of matching (matching degree) described later, when the specifications of the buyer data and the seller data match, the highest score (100 points in FIG. 5) is given as compared with other ranks. Has become.

On the other hand, the specifications belonging to rank B have relatively high importance, but the specifications belonging to rank B of the buyer data need not all coincide with the specifications of the seller data.
That is, among the specifications of the buyer data, there is no need for the seller data to have a specification that matches this. Here, the score when both match is lower than the rank A (30 in this example). Further, the specific numerical value of the specifications of the seller data is within a predetermined range (for example, ± a
%) Is regarded as “partial match”. The score in this case is set lower than the score when both match completely (15 in this example).

The specifications belonging to rank C have low importance, and the specifications of seller data need not all match the specifications belonging to rank C of buyer data. In addition, when both match, the points are lower than other ranks (5 points in this example).

Then, the control means (search means) 10 calculates the degree of matching of each specification (matching degree) based on such a search matrix, thereby obtaining the seller data which most satisfies the purchase conditions of the buyer. Search for. FIG.
Shows a search flow performed by the control means (search means) 10.

In this figure, the search means 10 assigns purchase specification information included in buyer data to ranks A, B, and C based on the search matrix (step 1000). In addition, the retrieval unit 10 uses the product name (or product category) included in the buyer data as a key and extracts seller data having the corresponding (same) product or category from the product information integration DB 20 (step 1010). . Then, the search means 10 narrows and searches the extracted seller data for those having specifications that match all of the specifications belonging to rank A of the buyer data (step 1020). For example, if the specifications belonging to the rank A of the buyer data are B1 and B2, the specifications B1 and B2
2. Extract the seller data having all the specifications that match 2.

Next, the search means 10 searches each of the narrowed-down searched seller data for a specification that matches the specification belonging to the ranks B and C of the buyer data, and follows the search matrix shown in FIG. Then, the degree of matching (matching degree) between the buyer data and the seller data is calculated by digitizing each seller data (step 1).
030). In addition, the search unit 10 appropriately searches for information on matching evaluation from past search results stored in the search result DB 6 (step 1040), and searches the evaluation DB 4 for buyer evaluation for the product or seller as appropriate (step 1040). Step 1050). Then, the search means 10
After appropriately converting these information into numerical values, the information is added to the degree of matching, and seller data that most satisfies the purchase conditions of the buyer is extracted based on the value (step 1040).

FIG. 7 specifically shows the processing of step 1030 described above.
1, sellers S1 to S2 having all specifications matching P2
4 are narrowed down and searched. And S1 to S
Regarding the data No. 4, it is searched whether there is a specification that matches the specifications P3 and P4 belonging to the rank B of the buyer data and the specification P5 belonging to the rank C, and the score based on the search matrix is displayed. For example, in the data of the seller S2, specifications Q13 and Q14 that partially match the specifications P3 and P4 of the buyer data are searched, and a predetermined score (15 points) is given. Similarly, a specification Q15 that completely matches the specification P5 of the buyer data is searched and assigned a score. In this figure, the display of the specifications of the buyer data is omitted for the data of S2 to S4.
By summing the scores at each rank in this way, the degree of matching (matching degree) between each data of S1 to S4 and the buyer data is calculated. In this example, the data of S1 and S2 have the highest degree of matching. (Total score 23
5).

FIG. 8 specifically shows the processing of the step 1040. The search means 10 searches the search result DB 6 for past search data on the product to be searched this time. In this figure, the search data includes the specifications of the products of sellers S100 and S200 that have transacted with the specifications P1 to P5 of the buyer data, and an index (matching evaluation) evaluated by the buyer with respect to the degree of matching (matching degree) of the goods. Contains. Then, from these data, the search means 10 finds that, for rank B, there is one seller specification that completely matches the buyer's specification (corresponding to the data in S100), so that the seller's specification that partially matches the buyer's specification is obtained. It can be seen that the two (corresponding to the data in S200) have higher buyer matching evaluation. Then, with reference to the matching evaluation, the value is added to the score of the matching degree of the data of S1 and S2 (by appropriately multiplying by a predetermined coefficient).

FIG. 9 specifically shows the processing of the step 1050. The search means 10 searches the evaluation DB 4 for past evaluation data on sellers S1 to S4 to be searched this time. Then, the search means 10 calculates the degree of matching in step 1030 from these data,
From S2, it is read that the seller S2 has a higher evaluation of the buyer. Then, referring to this evaluation, the value is added to the score of the matching degree of the data of S1 and S2 (by appropriately multiplying by a predetermined coefficient).

As described above, in addition to the matching degree calculated in step 1030, the past matching evaluation value for the corresponding product and the evaluation for the seller are quantified and added. The most satisfying seller data can be extracted. Then, every time a transaction is completed, the information in the evaluation DB and the search result DB is updated, and thereafter, the search for the desired product information that satisfies the buyer's purchase conditions is more quickly performed, and the matching degree is higher. You can search. In addition, the extracted seller data may be one having the highest numerical value,
Alternatively, a plurality of items may be extracted in descending order of numerical value.

After the seller data that best satisfies the buyer's purchase conditions is extracted as described above, the transaction may be established as the transaction price using the price specified by the buyer or the seller. May be determined. In particular, if there is more than one buyer or seller, an auction is performed to determine the transaction price,
It is convenient for buyers and sellers. FIG. 10 is a conceptual diagram showing a mode of determining a transaction price by an auction.

In this figure, it is assumed that both sellers S1 and S2 have products that satisfy the purchase conditions of buyers C1 to C4. Each seller has registered a “start price” and an “end price” corresponding to the “hammer price” in FIG. 2, and these indicate the set prices at the start and end of the auction, respectively. On the other hand, each buyer has registered the "designated purchase price" in FIG. 3, which indicates the buyer's desired purchase price. Then, for the seller S1, buyers C1 and C2 whose purchase specified price is higher than the start price of S1 and whose purchase specified price is lower than the end price are to be auctioned, and among the buyers C2 whose purchase specified price is higher. The transaction is established with. Similarly, for seller S2, S
The buyers C3 and C4 whose purchase specified price is higher than the start price and lower than the end price are purchase targets of the auction, and buyer C4 whose purchase specified price is higher among them.
A transaction is established between. Then, after the transaction is completed, FIG.
As described above, the settlement processing is appropriately performed.

Further, in the above-described embodiment, a case has been described in which the number of search means is one. However, a plurality of search means may be provided, and each search means may perform a search according to different criteria. In this case, since each search means has a different search matrix, different search results are presented to the same buyer. Then, in the search means information DB, for example, the degree of coincidence of the seller data with the purchase condition of the buyer is stored for each search means (or for each product), so that the buyer can perform the most reliable search based on this information. Can be selected.

The present invention is not limited to the embodiment described above. For example, each desired product information may not be stored in the product information integration DB, and the search means may access the information source of each desired product information every time a search is performed.
Also, after searching by the search means, without conducting an auction,
The price specified by the buyer or seller may be used as it is as the transaction price. Further, after calculating the degree of coincidence between the buyer data and the seller data along the search matrix, the seller data that most satisfies the purchase conditions of the buyer is referred to as the degree of coincidence without referring to the information in the evaluation DB or the search result DB. It may be determined accordingly. Also, instead of the seller recruiting page, the seller may be recruited by sending an e-mail to the address of the seller terminal.

The merchandise trading system of the present invention can be realized by a computer, various peripheral devices such as a communication device, and a software program executed by the computer, and a software program executed in the system. Can be distributed via a computer-readable storage medium or a communication line.

[0040]

As described above, according to the present invention,
The buyer only makes a predetermined purchase input to the system, and the system searches for the target seller. Therefore, the buyer does not need to access various auction sites by himself. In addition, the present system appropriately accesses other information sources (Web sites) and searches for sellers, so that the probability of finding the product desired by the buyer increases.

Then, since the product information having the sales specification information at least partially matching the buyer's purchase specification information is searched based on the desired product database, there is no product information that satisfies all the buyer's purchase conditions. In both cases, it is possible to quickly search the database for product information close to that with a high degree of coincidence.

Further, when the degree of coincidence between the purchase specification information and the sales specification information is quantified based on the ranking of the purchase specification information or the numerical value according to the degree of coincidence between the purchase specification information and the sales specification information, , The search can be quantified, and the desired product information that satisfies the buyer's purchase conditions can be searched more quickly and with a higher degree of coincidence. Furthermore, when a past search result or evaluation data for the corresponding product is referred to, the search becomes more accurate. In particular, each time a transaction is established, the information in the evaluation DB and the search result DB is updated, so that the reliability of subsequent searches increases.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a commodity trading system of the present invention.

FIG. 2 is a diagram showing a configuration of desired product information for sale (seller data).

FIG. 3 is a diagram showing a configuration of purchase desired product information (buyer data).

FIG. 4 is a diagram showing a flow of commodity sales.

FIG. 5 is a diagram showing an example of a search matrix.

FIG. 6 is a diagram illustrating a flow of a search process.

FIG. 7 is a diagram showing an aspect in which the degree of coincidence between buyer data and seller data is quantified.

FIG. 8 is a diagram illustrating an example of search data stored in a search result DB.

FIG. 9 is a diagram showing an example of evaluation data stored in an evaluation DB.

FIG. 10 is a conceptual diagram showing a method for determining a transaction price by an auction.

[Explanation of symbols]

2 Buyer information database (D
B) 2a Purchase desired product information (buyer data) 4 Evaluation database (DB) 6 Search result database (D
B) 8 Search information database (D
B) 10 control means (retrieval means) 12 input / output control means (transmission means) 22, 60, 62 merchandise desired database (DB) 22a desired merchandise information (seller data) 50 merchandise trading system 70, 72 buyer terminal 80, 82 Seller terminal 100 Network 110 Mobile communication network 200, 210 Other Web sites

Claims (9)

[Claims] When a buyer designates desired product information including a plurality of purchase specification information, a desired product database having one or more sales specification information is stored in correspondence with the seller information. And a search means for searching the desired product database for desired product information including sales specification information that at least partially matches the plurality of purchase specification information. . 2. The merchandise trading system according to claim 1, further comprising transmitting means for transmitting the desired product information searched by the searching means to the buyer terminal. 3. The merchandise trading system according to claim 1, further comprising the sales desired merchandise database. 4. The search specification database further comprising: ranking the purchase specification information, and storing numerical information according to the ranking or the degree of coincidence between the purchase specification information and the sales specification information. The search means, when predetermined sales specification information matches each purchase specification information, digitizes the degree of coincidence between each purchase specification information and the predetermined sales specification information based on the search information database. The merchandise trading system according to any one of claims 1 to 3, wherein information on desired merchandise that satisfies the purchase conditions of the buyer in the previous term is most searched. 5. The system according to claim 1, further comprising: an evaluation database storing evaluation information of the buyer with respect to a product or a seller for which a transaction has been made, wherein the search unit refers to the evaluation information in a subsequent search. Item 4. A commodity trading system according to any one of Items 1 to 4. 6. The apparatus according to claim 1, further comprising a search result database storing search results of said search means relating to products for which transactions have been established, wherein said search means refers to said search results in subsequent searches. Item 7. A commodity trading system according to any one of Items 1 to 5. 7. A plurality of search means, each of which has a different search criterion. When the buyer specifies the desired product information, it is possible to specify which search means to use for the search. The merchandise trading system according to any one of claims 1 to 6, wherein 8. The notifying means for notifying the purchase condition and the shortage amount of the buyer in the previous term and recruiting the seller when the number of desired products satisfying the purchase condition of the buyer in the previous term does not reach the desired purchase quantity of the buyer. The merchandise trading system according to any one of claims 1 to 7, further comprising: 9. A desired-sale product database in which, when a buyer designates desired-product information including a plurality of purchase specification information, desired-sale product information having one or more sales specification information is stored in correspondence with the seller information. And a step of searching the desired product database for desired product information including sales specification information that at least partially matches the plurality of purchase specification information.