JP2001350875A - Trend item predicting method and system device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a trend item predicting method and a system device for grasping a user group who finds a present trend item at first, and for proposing the latest item found by the user group as the next phase trend item. SOLUTION: This system is composed of a user behavior collecting device 1 set in a server B for identifying a user P, and for collecting and storing the action history of the identified user P, a history information analyzing device 2 for grasping and storing an original user P group who finds the present trend item in the early temporal stage from the action history, and a next term trend item predicting device 3 for grasping and storing the fact that the item found by the original user P is turned to be the latest item, and for grasping and storing the latest item found by the original user P group who finds the present trend item in the early temporal stage as a next term trend item, and for outputting this to a screen A3 of a communication terminal A2 of a contract user P.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and a system for processing a user's history information to predict an item that may become the next trend, and more particularly, to collect a user's action history as history information. The present invention relates to a method of selecting an item group that will become the next trend of a user, predicting the item group as the next trending item, and a system device directly used for implementing the method.

[0002]

2. Description of the Related Art Conventionally, as a method of predicting the next trending item, a method in which an item provider examines a small number of persons who own the current trending item by using a questionnaire or considers a few people It is a method of creating items by sharing items of wisdom and imagining items that will be sold in the next term.

[0003]

In the conventional method of predicting a trendy item, an item provider performs planning and the like with a small number of people inside, and grasps later trends of users and plans the planning. Can not be reflected from. This is because the questionnaire can be taken only for a small number of users and the user who first found and spread the currently popular item could not be identified.

Here, the main objects to be solved by the present invention are as follows. That is, the first object of the present invention is to grasp the group of users who first found the current fashion item by assuming that the user who found the current fashion item before fashion became popular also found the next fashion item. It is an object of the present invention to provide a fashion item prediction method and a system device for suggesting the latest item found by the user group as the next fashion item.

[0005] A second object of the present invention is to allow a service provider to predict and plan a more user-friendly item by selecting a trendy item mainly composed of web users. It is an object of the present invention to provide a trendy item prediction method and a system device.

A third object of the present invention is a trendy item prediction method for presenting items in real time based on information closer to the user's position, with items being watched by a group of fashion finder from the latest page. And system devices.

[0007] Other objects of the present invention will become apparent from the description of the specification, drawings, and particularly the description of each claim in the appended claims.

[0008]

In order to solve the above-mentioned problems, the method of the present invention is a method for finding the next fashionable item in consideration of the actual situation of electronic commerce and the like via a telephone network, and is a popular method. Of the people who found the item early on the item group, the people whose information is fashionable at this time are regarded as fashionable item discoverers, and the information that few people other than the fashionable item discoverers have accessed is the next term. Take a characteristic method of predicting as fashionable item information.

[0009] In order to solve the above-mentioned problems, the apparatus of the present invention can identify a means for identifying a user in a system for finding the next trending item through electronic commerce between a client and a server via a communication network. A means to collect the user's activity history, a means to identify the group of users who have found the trendy items at the beginning of the current time, and that the items seen by the user are the latest items. Means for constructing a system including means for identifying, and a next trending item, a storage means, and a means for outputting the latest item viewed by a group of users who have found the trendy item at the beginning at the present time. Take.

[0010] More specifically, the object of the present invention is attained by employing the following novel characteristic construction methods or means of the present invention.

A first feature of the method according to the present invention is that when a next trending item is found from user history information which communicates user access and product / service purchase to a service side via a communication network, a popular item group is used. Out of the users who have found the item earlier, the users whose information is currently in fashion are considered as fashionable item discoverers, and the latest information that the fashionable item The present invention resides in adopting a configuration of a trendy item prediction method for predicting, as next trendy item information, information to which only a small number of users other than the discoverer group have accessed.

A second feature of the method of the present invention is that the communication network in the first feature of the method of the present invention is one or more of a telephone line network, an optical communication network, ISDN, DSL, ADSL, and WLL. Built Internet, virtual private network, LA
The present invention resides in adopting a configuration of a fashion item prediction method including one or more of N, WAN, and GAN.

According to a third feature of the method of the present invention, the user history information to be communicated in the first or second feature of the method of the present invention is an access log from a user and a product / service purchase log. It is in the adoption of the configuration of the fashion item prediction method.

A fourth feature of the method of the present invention is that the user history information in the first, second or third feature of the method of the present invention is a fashion item prediction method in which the user history information is directly collected from the service side. Configuration adoption.

According to a fifth feature of the method of the present invention, the fashion item in the first, second, third or fourth feature of the method of the present invention is such that the service side previously sets a threshold value of the number of user accesses. Then, the present invention is to adopt a configuration of a fashionable item prediction method that is an item exceeding the threshold value.

According to a sixth feature of the method of the present invention, the latest item in the first, second, third, fourth or fifth feature of the method of the present invention is such that the service side determines in advance the date and time or It is set to be several hours before the day, and the configuration of the fashionable item prediction method which is an item closer to the present than that time is adopted.

[0017] A seventh feature of the method of the present invention is that the user in the first, second, third, fourth, fifth or sixth feature of the method of the present invention has a special contract with the service side. And
The present invention resides in adopting a configuration of a fashion item prediction method in which a usage fee is paid and the fashion item is introduced.

[0018] An eighth feature of the method of the present invention is that the usage fee in the seventh feature of the present method is one of a flat-rate system and a usage-based system of the amount of the trendy items to be introduced. It consists in adopting the configuration of the method.

According to a ninth feature of the method of the present invention, the introduction of the trendy item in the seventh feature of the method of the present invention includes the introduction of the trendy item from the entire item group, the genre and the like.
Trendy item prediction which is either introduction of trendy items in user attributes / conditions specified and introduction of trendy items of users accessing the group of items based on the specified item group It consists in adopting the configuration of the method.

According to a tenth feature of the method of the present invention, the introduction of the trendy item in the seventh, eighth or ninth feature of the method of the present invention is such that items viewed by the group of trendy item discoverers are displayed in chronological order. Or adopting a configuration of a trendy item prediction method in which one of the items viewed by the trendy item finder is displayed to the user in the order of the fashionable possibility, which is displayed in the order of what many fashionable item finder has viewed. It is in.

A first feature of the apparatus of the present invention is that a client and a server for finding the next trending item from user action history information for communicating user access and product / service purchase to a service side via a communication network are described. A user behavior collection device that is installed on the server and that identifies and identifies the user and collects and stores the identified user's action history. A history information analysis device that grasps and accumulates the original user group found at the beginning, and grasps and accumulates that the item seen by the original user is the latest item, and also stores the current trendy item at the beginning. The latest item found by the original user group found in the above is grasped and accumulated as the next trending item, and it is stored in the client. And next trend item predicting device for outputting the bets, in in the configuration adopting formed by the system constructed epidemic item prediction system device.

A second feature of the apparatus of the present invention is that the client in the first feature of the apparatus of the present invention is a cookie for connecting to the communication network and logging in the user.
The present invention resides in the configuration and adoption of a trendy item prediction system device having a browser-equipped communication terminal using e.

A third feature of the apparatus of the present invention is that the user behavior collecting apparatus according to the first or second feature of the present invention is configured such that an access log of a user of the client, a product / service log, etc. The Web information collection unit to be collected and the user ID to identify the user
UserID issuing unit and UserI for allocating and managing
D identification management unit, an Item issuing unit that allocates and manages Item IDs for each item to identify the items, and an I
itemID identification management unit, and the corresponding UserID and Item
UserID, ItemI for accumulating access time and page address history information related to ID in a database
D, an access time accumulating unit, an Item ID, and a page address accumulating unit.

A fourth feature of the apparatus of the present invention is that the history information analyzing apparatus according to the first, second or third feature of the apparatus of the present invention is popular among history information accumulated by the user behavior collecting apparatus. A section for grasping N popular web information and a section for accumulating N popular web information for grasping pages, and an original user m grasping section and m original users for grasping original users who accessed the popular page at the beginning. The present invention resides in the configuration and adoption of a fashionable item prediction system device organically configured with a storage unit.

A fifth feature of the apparatus of the present invention is that the next trend item predicting apparatus according to the first, second, third or fourth feature of the present apparatus has a history accumulated by the user behavior collecting apparatus. A latest web page grasping unit and a latest web page accumulating unit for grasping and accumulating the latest web page information from the information; and the latest web page information from the original user information and the latest web page information accumulated by the history information analysis device. The latest page original user access information grasping unit and the latest page original user access information storage unit that grasp and accumulate the information accessed by the original user, and the next trending items are arranged in the order of possible fashion from the latest page original user access information. Rearrangement section for next fashionable items that can be sorted and accumulated And sex order storage unit, in the configuration adopting the next pandemic and next pandemic item output unit for outputting display items information to the communication terminal of the client who contracts in vogue item prediction system apparatus organically configured.

In the present invention, since the above-mentioned configuration method and means are adopted, each user is provided with an ID (UserID) for identifying the user himself / herself in the user behavior collection device.
It is given and managed by the serID issuance / identification management unit. Each item has an ID (ItemID) for individually identifying the item in the user behavior collection device.
It is given and managed by the ID issuing / identifying management unit.

Using these two IDs, mapping between individuals and items is performed. Individual item (ItemID)
User who first accessed to UserID, Item
Item in mID, access time / page address storage unit
It is stored as a group of mID and UserID.

In the history information analysis device, in the grasping / accumulating section of N popular web information, its UserID, ItemI
D, N popular items from the access time / page address storage unit, and retrieves m original users and stores the items and the original user group of the person who first accessed the item in the storage unit as a set. I do.

The latest page original user access information comprehension / accumulation unit of the next trend item prediction device is used to identify those who are currently viewing the trendy items (most popular items) in the accumulated item group. , Elected as a group of epidemic discoverers. The latest item accessed by the selected fashion discoverer group is used as a prediction means as the next trend item.

[0030]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings with reference to an apparatus example and a method example. In addition,
In the embodiment, the telephone line network, the optical communication network, the ISDN,
The description mainly focuses on the Internet constructed with DSL, ADSL, WLL or the like, but is not limited thereto. Needless to say, other virtual private networks, LANs, WANs, GANs and the like are also possible.

(Example of Apparatus) FIG. 1 is a configuration block diagram showing an entire system apparatus of this example of apparatus. In the figure, A is a client and has a communication terminal A2 equipped with a browser A1 operated by a user P, B is a server that provides services S such as goods and services, and C is a client that connects the client A and the server B. Is the Internet.

Α is a fashion item prediction system device of the present device example, which is installed in the server B, identifies the user P, and collects and accumulates the identified user P's action history. Apparatus 1, a history information analysis apparatus 2 that grasps and accumulates a group of original users P who found a trendy item at the present time earlier from the action history, and an item that the original user P saw is the latest. The latest items seen by the group of original users P who found the current fashion item at the beginning are grasped and accumulated as the next fashion item and output to the client. And the next trend item prediction device 3 to be constructed.

The user behavior collection device 1 includes a web information collection unit 1a that collects access logs, merchandise / service logs, and the like of the user P of the client A, and a User ID for identifying the user P to the user. UserID issuing unit 1b 'and UserID identification managing unit 1b "for allocating and managing, ItemID issuing unit 1c' and ItemID identifying and managing unit 1c" for allocating and managing ItemID to each item for identifying the item, and the UserID and ItemID Us to accumulate access time and page address history information related to the database in the database
erID, ItemID, access time accumulating unit 1d 'and ItemID, page address accumulating unit 1d ".

The history information analysis device 2 grasps and accumulates popular pages from the history information accumulated by the user behavior collection device 1 and stores N popular web information and 2N ″ popular web information. And an original user m grasping unit 2b 'and an original user m storing unit 2 for grasping and accumulating the original user P who has accessed the popular page.
b "and organically.

The next trend item prediction device 3
The latest web page grasping section 3a 'and the latest web page accumulating section 3a "for grasping and accumulating the latest web page information from the history information accumulated by the user behavior collecting apparatus 1, and the original information accumulated by the history information analyzing apparatus 2. Latest page original user access information grasping unit 3 for grasping and accumulating the information accessed by the original user P on the latest page from the user information and the latest web page information.
b 'and the latest page original user access information storage unit 3b ", and the next trending item trending possibility sorting unit 3c' for sorting and storing the next trending items in the trending possibility order from the latest page original user access information.
And the next trending item fashionable order accumulating unit 3c ″ and the next trending item output unit 3d that outputs and displays the next trending item information on the communication terminal A2 of the client A who has contracted.
And organically.

(Example of Method) An example of a method according to the present embodiment applied to the above-described apparatus will be described. First, a procedure for collecting and identifying items will be described. In the user history information collection device 1, the web information collection unit 1a receives the access log or the product / service purchase log of the user P from the server B side, and receives this service for the first time.

Since the web user P must acquire an ID necessary to identify the user P himself (there is no User ID), ST1 and ST2 in FIG.
A message and an acknowledgment button A4 are displayed on the screen A3 of the communication terminal A2 as shown in FIG. 3, and it is confirmed whether registration for receiving the service is permitted. When the acknowledgment button A4 is clicked, the user ID is clicked. A user ID is assigned to each user P from the issuing unit 1b ', and the user ID is identified and managed by a user ID identification management unit 1b ".

At this stage, in one embodiment, in order to provide a unique UserID for each web browser A1, C
Use cookie. Cookie is Client A
Is maintained. If Cookie is used, the server B stores information unique to each client A on each communication terminal A2, and the client A
Or, when a specific page is referred again, the information can be used.

Also, by using the Cookie mechanism, the server B can customize a web page for each client A and store a web history of a specific client A.

Next, as shown in FIG. 4, the web page accessed by the user P is collected by the web information collecting unit 1a (STa). In accumulating this web page,
After going through STa to STd in FIG. 4, it is determined whether the UserID and the Web information have an ItemID (STb),
If not, issue setting is performed by the Item ID issuing unit 1c '(ST
c) Then, if there is, the ID is managed by the Item ID identification management unit Ic ″.

The UserID, ItemID, and access time set are stored in the UserID, ItemID, access time storage unit 1d '(STd), and are stored in the ItemID, web page set in the ItemID, page address storage unit 1d''.

Next, a procedure for setting conditions for introducing trendy items will be described with reference to FIGS.

(Method Example 1) Example of Introducing Popular Items from All Items Group Popular Web Information N Items Grasping Unit 2 a ′ of History Information Analysis Device 2
Identifies N popular web pages from all the web pages obtained by the user behavior collection device 1 and
Is acquired (STA), n persons who have accessed each web page first are grasped (STB) and stored in the N popular web information storage unit 2a ″.

The original user m-person grasping unit 2b 'grasps the m persons who recognized the currently popular page fastest among n persons of each of the popular N web pages, It is stored in the original user m-person storage unit 2b ″.

The latest web page grasping unit 3a 'and the latest web storage unit 3a "of the next trend item prediction device 3
Continuously grasps and accumulates the latest web page information from the user behavior collection device 1. In parallel with this, as shown in FIG. 7, the latest page original user access information grasping unit 3b ′ and the latest page original user access information storage unit 3b ″ of the next trend item prediction device 3 are m
The latest web page among web pages accessed by a person is grasped (STI), and the web page is stored.

The next fashionable item fashionable order sorting unit 3c 'and the next fashionable item fashionable order storage unit 3c "
Will use the accumulated web page as the next trending item,
The items are rearranged in the order of fashion possibility according to the procedure mode of STII and STIII, and are output from the next fashionable item output unit 3d to the screen A3 of the communication terminal A2 of the contract client A. This is stored as an example of an embodiment that sorts by epidemic possibility (STIV).
M pages are output in the order of the latest web page among the pages that the fashion finder has seen more (see FIG. 8).

(Method Example 2) Example of Introducing Trendy Items in Web Page Genre / Attribute of Contract Users Who Use This Service by Designating the Genre etc. FIG. 9 shows the next trend predicting apparatus α. FIG. 4 is a model diagram for explaining a communication procedure of the example of the method using the method.

As shown in the figure, the contract user P designates the genre (eg, cosmetics, clothes, etc.) and attributes of the web page as the prediction range condition designation, and thereafter, based on the designated genres and attributes, Is performed by the next item predicting apparatus α. As the processing, n popular web pages are accessed, and each web page is first accessed.
Understand people.

From among the n popular N web pages for each page, the m people who recognized the currently popular page first are identified. The latest web page among the web pages accessed by m persons is grasped and the web page is accumulated.

The stored web pages are sorted as the next trending items in the order of the likelihood of fashion, a predicted trend item list is created, and the list is output to the screen A3 of the communication terminal A2 of the contract client A. As an example of sorting according to the fashion possibility, M pages are output in the order of the latest web page in the specified genre / attribute in a page which is more frequently viewed by a fashion discoverer.

Thereafter, the user P of the contract client A
Pays for the amount of information delivered or a fixed fee to the service provider of the server B, and establishes a business. The parallel item prediction system apparatus α in FIG. 1, the flowcharts in FIGS. 2, 4, 6, and 7, the output screens in FIGS. 3 and 8, and the images in FIG.
The same applies.

(Method Example 3) Trendy Item Introduction Example Based on the Specified Item The m persons who first accessed the specified web page are grasped. The latest web page among the web pages accessed by m persons is grasped and the web page is accumulated.
The stored web pages are sorted as fashionable items in the order of possible fashion and output to various services.
As an embodiment of sorting in order of fashion possibility, M pages are output in the order of the latest web page in pages that are more frequently viewed by fashion discoverers.

It should be noted that the trendy item prediction system device α of FIG. 1, the flowcharts of FIGS. 2, 4, 6, and 7, the output screens of FIGS. 3 and 8, and the images of FIG. The same applies to Method Example 1.

In the above-mentioned method examples 1 to 3, when the user P of the client A receives an introduction of a trendy item from the server B (displayed on the screen A3 of the communication terminal A2 of the client A), a special contract for paying a usage fee is made. This usage fee may be a monthly flat-rate system or a pay-as-you-go system for the amount of trendy items to be introduced.

As the communication terminal in this embodiment, a personal computer, a mobile phone, a PHS or the like is used. The representative apparatus examples and method examples of the present invention have been described above, but the present invention is not necessarily limited to only the means of the apparatus examples and the methods of the method examples. The present invention achieves the object of the present invention, and can be implemented with appropriate modifications within a range having the effects described below.

[0056]

As described above, the present invention has been able to predict the next fashionable item only in a state in which only the thoughts of a small number of item providers and a small number of users are reflected to date. As a result, the interest trends of the majority of users can be grasped.

In particular, the history information of the web user who preempts the current fashion item is handled, and the latest item is taken out of the history information, so that the item which can become the next fashion item can be more on the user side. The service side can make predictions from a standpoint, and make a preemptive item strategy for it.

Since the user's action history information can be tracked in chronological order, it can be applied to the analysis of the user's action tendency, knowledge management, and the like. In addition, the present invention has an excellent effect that it can be applied as a selection criterion for concluding a partner contract with a new company which is likely to look promising for the next trend item and the like.

[Brief description of the drawings]

FIG. 1 is an overall configuration block diagram of an example of an apparatus showing an embodiment of the present invention.

FIG. 2 is a flowchart for acquiring a UserID in the example of the method.

FIG. 3 is an ID acquisition image for identifying a user in the above.

FIG. 4 is a flowchart for accumulating UserID and ItemID in the above.

FIG. 5 is an image diagram in Method Example 1 of the same.

FIG. 6 is a flowchart for extracting a user who first accessed an arbitrary web page in the above.

FIG. 7 is a flowchart for rearranging the items in the same order as in the next fashion.

FIG. 8 is a next trend output image of the above.

FIG. 9 is a model diagram illustrating a communication procedure in Method Example 2;

[Explanation of symbols]

A: Client A1: Browser A2: Communication terminal A3: Screen A4: Accept button B: Server C: Internet S: Service P: User α: Trendy item prediction system device 1: User behavior collection device 1a: Web information collection unit 1b '... UserID issuing unit 1b "... UserID identification managing unit 1c' ... ItemID issuing unit 1c" ... ItemID identification managing unit 1d '... UserID, ItemID, access time storage unit 1d "... ItemID, page address storage unit 2 ... History information Analysis device 2a ': N popular web information grasping unit 2a "... N popular web information accumulating unit 2b' ... Original m user grasping unit 2b" ... Original m user accumulating unit 3: Next trend item prediction device 3a '... Latest web page grasping unit 3a "... Latest web page storage unit 3 b ': Latest page original user access information grasping section 3b "... Latest page original user access information storage section 3c' ... Next trending item fashion possibility sort ordering section 3c" ... Next fashion item fashion possibility sort storage section 3d … The next trending item output section

Claims (15)

[Claims] 1. To find the next fashionable item from user history information that communicates user access and product / service purchase to the service side via a communication network, quickly find the item in a popular item group Of the users whose information is in fashion at the current time, it is regarded as a fashionable item discoverer group, and users other than the fashionable item discoverer group are the latest information viewed by the fashionable item discoverer group. A trendy item prediction method, wherein information that is accessed only by a small number is predicted as next trending item information. 2. The communication network includes a telephone line network, an optical communication network, ISDN, DSL, ADSL,
2. The fashionable item prediction method according to claim 1, further comprising at least one of an Internet, a virtual private network, a LAN, a WAN, and a GAN constructed by one or more of WLLs. 3. The fashion item prediction method according to claim 1, wherein the user history information to be communicated is an access log from a user and a product / service purchase log. 4. The fashion item prediction method according to claim 1, wherein the user history information is directly collected from the service side. 5. The trendy item according to claim 1, wherein the service side previously sets a threshold value of the number of accesses of the user, and the item exceeds the threshold value. Fashion item prediction method. 6. The item as set forth in claim 1, wherein the latest item is an item that is set in advance by the service side to a date and time or a few days before the present time, and is closer to the present than that time. 3. The fashion item prediction method according to 3, 4, or 5. 7. The user according to claim 1, wherein the user specially makes a contract with the service side, pays a usage fee, and receives an introduction of the fashionable item. 6. The fashion item prediction method according to item 6. 8. The fashion item prediction method according to claim 7, wherein the usage fee is one of a fixed-rate system and a usage-based system of the amount of the fashion item to be introduced. 9. Introducing the trendy item is to introduce a trendy item from all the item groups, introduce a trendy item in the genre / attribute / condition of the user by designating the attribute / condition, and specify the designated item group. 8. The trendy item prediction method according to claim 7, wherein the trendy item is one of introductions of trendy items of a group of users accessing the group of items. 10. The trendy item introduction may be performed by displaying items viewed by the trendy item discoverer group in chronological order, or by watching a trendy item discoverer among many items viewed by the trendy item discoverer. 10. The trendy item prediction method according to claim 7, 8 or 9, wherein any one of the items that are displayed in the order of the items that are present is displayed in the order of the likelihood of fashion and presented to the user. 11. A system for connecting a client and a server for finding an upcoming trendy item from user action history information that communicates user access and product / service purchase to a service side via a communication network via a communication network. A user behavior collection device that is installed on the server and that collects and accumulates the user's behavior history that identifies the user and identifies the user, and an original that finds the current trendy item early in time. A history information analysis device that grasps and accumulates the user group, and the original user group that grasps and accumulates that the item viewed by the original user is the latest item and finds the current trendy item at the beginning The next workout that grasps and accumulates the latest item that is being viewed as the next trending item and outputs it to the client And a trending item prediction system device, which is constructed by the following. 12. The client according to claim 1, wherein said client is connected to said communication network and said user logs in.
The trendy item prediction system device according to claim 11, further comprising a communication terminal equipped with a browser that uses an cookie. 13. The user behavior collection device, wherein a web information collection unit that collects access logs, merchandise / service logs, and the like of the user of the client, and allocates a User ID to the user to identify the user. A UserID issuing unit and a UserID identification managing unit to manage, an ItemID issuing unit and an ItemID identification managing unit to allocate and manage an ItemID to each item for identifying the item, and access time and page address history information relating to the UserID and the ItemID. 13. The trendy item prediction system device according to claim 11, wherein the user ID, the Item ID, the access time storage unit, the Item ID, and the page address storage unit are stored in a database. 14. The history information analysis device, comprising: a popular web information N-item grasping unit and a popular web information N-item accumulation unit for grasping a popular page from the history information accumulated by the user behavior collecting device; 14. An original user m-person grasping unit for grasping an original user who accessed at the beginning and an original user m-person accumulating unit, and organically constituted by: The described trendy item prediction system device. 15. The latest trend item predicting device, comprising: a latest web page grasping unit and a latest web page accumulating unit for grasping and accumulating the latest web page information from the history information accumulated by the user behavior collecting device; The latest page original user access information grasping unit and the latest page original user access for grasping and accumulating the information accessed by the original user on the latest page from the original user information and the latest web page information accumulated by the analyzer. An information storage unit, a next trending item trending order sorting unit that sorts and stores the next trending items from the latest page original user access information in order of trending possibility, and a next trending item trending possibility order storage unit; The communication terminal of the client who has contracted the trendy item information The trendy item prediction system device according to claim 11, 12, 13 or 14, wherein the trendy item output unit for outputting and displaying the information is organically configured.