Merchandise Recommendation System, Method and Non-Transitory Computer Readable Storage Medium of the Same for Multiple Users

A merchandise recommendation method for multiple users used in a merchandise recommendation system including a user database, a merchandise database, a data transmission module, a processing module and a memory is provided. The merchandise recommendation method includes the steps outlined below. The processing module receives participant information and target merchandise information from a remote originator host. The processing module retrieves corresponding user information from the user database according to the participant information. The processing module retrieves corresponding merchandise information from the merchandise database according to the target merchandise information. The processing module analyzes social influence information and preference information included in the user information and analyzes the merchandise information to generate an analysis result. The processing module generates composite merchandise recommendation information according to the analysis result.

RELATED APPLICATIONS

This application claims priority to Taiwan Application Serial Number 102140503, filed Nov. 7, 2013, which is herein incorporated by reference.

BACKGROUND

1. Field of Invention

The present invention relates to a recommendation technology. More particularly, the present invention relates to a merchandise recommendation system, a method and a non-transitory computer readable storage medium of the same for multiple users.

2. Description of Related Art

Buying travel services and group-buying are two main commercial activities in modern life. Consequently, online websites for providing traveling and shopping information that have large databases becomes popular. It is convenient for the users to access the websites and take the information in the databases as reference.

Take buying travel services as an example, when the online resources are used to organize the trip, the information that the websites or the systems mentioned above provide is designed for a single person. However, in practical situation, there are often a multiple of participants in the trip. One of the participants may inquire of other participants' opinions, make discussion with all the participants and start to use the websites or the systems to make travel plans after the discussion. The process of discussion is time-consuming and exhausting. Likewise, if a group of participants want to buy a combination of merchandises, similar discussion has to be made to satisfy the needs of all the participants. Since the participants have their own preference respectively, the process of discussion is also time-consuming.

Accordingly, what is needed is a merchandise recommendation system, a method and a non-transitory computer readable storage medium of the same for multiple users to address the issues mentioned above.

SUMMARY

The invention provides a merchandise recommendation system including a user database, a merchandise database, a data transmission module, a processing module and a memory. The user database stores a plurality pieces of user information. The merchandise database stores a plurality pieces of merchandise information. The processing module is coupled to the user database, the merchandise database and the data transmission module. The memory stores a plurality computer-executable commands and is coupled to the processing module. When the commands are executed by the processing module, the processing module performs the steps outlined below. A piece of participant information related to a group of participants and a piece of target merchandise information are received from a remote originator host through the data transmission module. A plurality of pieces of corresponding user information are retrieved from the user database according to the participant information. A plurality pieces of corresponding merchandise information are retrieve from the merchandise database according to the target merchandise information. A piece of social influence information included in the corresponding user information and a piece of preference information related to the corresponding merchandise information are analyzed to generate an analysis result. A piece of composite merchandise recommendation information is generated according to the analysis result.

Another aspect of the present invention is to provide a merchandise recommendation method used in a merchandise recommendation system including a user database, a merchandise database, a data transmission module, a processing module and a memory, wherein the processing module is coupled to the user database, the merchandise database, the data transmission module, the processing module and the memory. The merchandise recommendation method includes the steps outlined below. A piece of participant information related to a group of participants and a piece of target merchandise information are received from a remote originator host through the data transmission module by the processing module. A plurality of pieces of corresponding user information are retrieved from the user database according to the participant information by the processing module. A plurality pieces of corresponding merchandise information are retrieve from the merchandise database according to the target merchandise information by the processing module. A plurality of social influence information included in the corresponding user information and a piece of preference information related to the corresponding merchandise information are analyzed to generate an analysis result by the processing module. A piece of composite merchandise recommendation information is generated according to the analysis result by the processing module.

Yet another aspect of the present invention is to provide a non-transitory computer readable storage medium to store a computer program to execute a merchandise recommendation method used in a merchandise recommendation system. The merchandise recommendation system includes a user database, a merchandise database, a data transmission module, a processing module and a memory, wherein the processing module is coupled to the user database, the merchandise database, the data transmission module, the processing module and the memory. The merchandise recommendation method includes the steps outlined below. A piece of participant information related to a group of participants and a piece of target merchandise information are received from a remote originator host through the data transmission module by the processing module. A plurality of pieces of corresponding user information are retrieved from the user database according to the participant information by the processing module. A plurality pieces of corresponding merchandise information are retrieve from the merchandise database according to the target merchandise information by the processing module. A social influence information included in the corresponding user information and a piece of preference information related to the corresponding merchandise information are analyzed to generate an analysis result by the processing module. A piece of composite merchandise recommendation information is generated according to the analysis result by the processing module.

DETAILED DESCRIPTION

FIG. 1is a block diagram of a merchandise recommendation system1in an embodiment of the present invention. The merchandise recommendation system1includes a user database100, a merchandise database102, a data transmission module104, a processing module106and a memory108.

The user database100stores a plurality pieces of user information101. In an embodiment, the user information101includes user names, user-related profiles, social information and history records related to the merchandises. The user-related profile includes such as, but not limited to the alma mater, the occupation, the title and the hobbies of the user. The social information includes such as, but not limited to social activities and friends of the user. In different embodiments, the user information101includes data manually inputted by the users, the interactive data of the users in a social network website, and the history records of surveying and purchasing the merchandises.

The merchandise database102stores a plurality pieces of merchandise information103. In an embodiment, if the merchandises that the merchandise recommendation system1recommends are related to traveling, the merchandise information103may include such as, but not limited to a piece of sightseeing spot information, a piece of traffic information, a piece of board and lodging information or a combination of the above. In another embodiment, if the merchandises that the merchandise recommendation system1recommends are related to food, the merchandise information103may include such as, but not limited to pineapple cakes from a first brand, egg rolls from a second brand, cookies from a third brand or a combination of the above. It is noted that, the merchandise information103may include other types of merchandises depending on practical demands and is not limited to the exemplary merchandises mentioned above.

The data transmission module104can be any module that provides an interface for the processing module106to communicate to other devices, such as but not limited to wired or wireless network data transmission module. The data transmission can be performed by using any possible form or specification of network communication.

The processing module106is coupled to the user database100, the merchandise database102and the data transmission module104. The processing module106can be any processor that has the ability to perform data operation. The processing module106performs data transmission with the databases and the modules described above by using different types of data transmission paths. In different embodiments, the memory108can be such as, but not limited to a ROM (read-only memory), a flash memory, a floppy disc, a hard disc, an optical disc, a flash disc, a tape, an database accessible from a network, or any storage medium with the same functionality that can be contemplated by persons of ordinary skill in the art to which this invention pertains. The memory108stores a plurality of computer-executable commands105and is coupled to the processing module106. The processing module106is able to execute the commands105to perform and provide the functions of the merchandise recommendation system1. The operations of the processing module106during the execution of the commands105are described below.

The processing module106receives a piece of participant information131related to a group of participants and target merchandise information133from a remote originator host130through the data transmission module104. Take the merchandises related to traveling as an example, the remote originator host130is operated by an originator to transmit the participant information131and the target merchandise information133. The participant information131includes the user names of the participants or other related information. In an embodiment, the originator is also one of the participants. The target merchandise information133includes such as, but not limited to the sightseeing spots, the transportations, the places for boarding and lodging or a combination of the above.

The processing module106retrieves pieces of corresponding user information107from the user database101according to the participant information131. Further, the processing module106retrieves corresponding merchandise information109from the merchandise database102according to the target merchandise information133. The corresponding user information107is the user information of the participants mentioned above. The corresponding merchandise information109is the merchandise information related to the target merchandise information133.

The processing module106further analyzes social influence information included in the corresponding user information107and preference information related to the corresponding merchandise information109to generate an analysis result. Subsequently, the processing module106generates composite merchandise recommendation information111according to the analysis result. In an embodiment, the processing module106transmits the composite merchandise recommendation information111to remote participant hosts132aand132bcorresponding to the group of participants through the data transmission module104. As described above, in some embodiments, the processing module106also transmits the composite merchandise recommendation information111to the remote originator host130since the originator can also be one of the participants.

It is noted that the number of the remote participant hosts can be different depending on the practical condition and is not limited to the embodiment illustrated inFIG. 1.

Consequently, the merchandise recommendation system1of the present invention can integrate the user information of a multiple of participants and the related target merchandise information to generate the composite merchandise recommendation information that matches the demands of the multiple participants.

For example, if a user A invites a user B to travel to the west coast of United States, the user A is supposed to be the originator that sends the participant information131and the target merchandise information133to the merchandise recommendation system1. The participant information131includes the user name and the related information of the user A and the user B. The target merchandise information133may include such as, but not limited to the sightseeing spots in the west coast such as the Space Needle in Seattle, the Disney Land in Los Angles or the Alcatraz Island in San Francisco, or the information of the airline companies, shuttle buses, hotels or restaurants.

The processing module106retrieves the corresponding user information107and the corresponding merchandise information109and performs analysis thereon. The analysis result of the corresponding user information107may show that the user A likes amusement fields and cultural spots, prefers activities that cost less money but does not like music performances. Further, the user A requires a high standard of boarding and lodging conditions. On the other hand, the analysis result of the corresponding user information107may show that the user B likes cultural spots and music performances but hates amusement fields. Further, the user B does not care about the cost but has no special requirement of boarding and lodging conditions. The processing module106calculates the preference value of the user related to each of the corresponding merchandise information133to further select the target merchandises that match the needs of both the user A and the user B to generate the composite merchandise recommendation information111. In an embodiment, the processing module106also analyzes the correlation of the corresponding merchandise information109, such as the distances between each of the sightseeing spots and the time that the user may stay in the sightseeing spots, to generate the composite merchandise recommendation information111that is arranged in a time schedule form.

FIG. 2Ais a diagram of the preference values related to different merchandises C1, C2, C3, C4and C5of the user A and the user B in an embodiment of the present invention.FIG. 2Bis a diagram illustrating the social influence between the user A and the user B in an embodiment of the present invention.

The preference values related to the merchandises C1, C2, C3, C4and C5of the user A are 0.2, 0.8, 0, 1 and 0.5 respectively, as illustrated inFIG. 2A. The preference values related to different merchandises C1, C2, C3, C4and C5of the user B are 0.3, 0.5, 1, 1 and 0.2 respectively, as illustrated inFIG. 2A. In the present embodiment, the processing module106further takes the social influence illustrated inFIG. 2Binto consideration, such that the social influence is used as a weighting factor to calculate the weighted preference values to match the needs of the user A and the user B. In different embodiments, the parameters of the social influence are either inputted by the originator or are obtained according to the social relation of the participants (e.g. the user A and the user B in the present embodiment). For example, if the user A and the user B are a couple and the interactions on the social network websites show that the user B mostly agrees with the decisions made by the user A, and the user A seldom agrees with the decisions made by the user B, the processing module106determines that the user A has a greater social influence over the user B.

In the example illustrated inFIG. 2B, the social influence of the user A over the user B is 0.8, and the social influence of the user B over the user A is 0.1. The social influence of a user to his/her own is 1. Therefore, the influence weighting parameter of the user A is calculated as (1+0.8)/2=0.9, and the influence weighting parameter of the user B is (1+0.1)/2=0.55.

Before the factor of the social influence is taken into consideration, the processing module106directly averages the preference values related to the merchandises C1, C2, C3, C4and C5of the user A and the user B shown inFIG. 2Aand obtains the values of 0.25, 0.65, 0.5, 1 and 0.35. After the factor of the social influence is taken into consideration, the processing module uses the influence weighting parameters of 0.9 and 0.55 of the user A and the user B respectively to calculate weighted preference values of 0.24, 0.69, 0.38, 1.2 and 0.39. The composite merchandise recommendation information111is further generated according to the weighted preference values.

Accordingly, after the factor of the social influence is taken into consideration, the merchandise recommendation system1generates the composite merchandise recommendation information with high efficiency and high accuracy to match the needs of the participants.

FIG. 3is a block diagram of the merchandise recommendation system1in an embodiment of the present invention. Similar to the merchandise recommendation system1illustrated inFIG. 1, the merchandise recommendation system1illustrated inFIG. 3includes a user database100, a merchandise database102, a data transmission module104, a processing module106and a memory108.

In the present embodiment, the processing module106receives editing information301from one of the hosts corresponding to the group of the participants through the data transmission module104to edit the composite merchandise recommendation information111. In an embodiment, the processing module106further transmits the edited composite merchandise recommendation information111′ to each of the participants through the data transmission module104.

The processing module106further receives suggestion information303from remote non-participant hosts300and302corresponding to the users not in the group of participants through the data transmission module104. The processing module106further transmits the suggestion information303to the remote participant hosts132aand132b. In another embodiment, the suggestion information303is retrieved from a social network database304included in the merchandise recommendation system1by the processing module106.

For example, if a user that is not one of the participants surveys the composite merchandise recommendation information111and thinks that part of the schedule costs too much, takes too much time or brings bad memory according to its experience, the user can send the suggestion information303such that the participants can take the suggestion information303into consideration. On the other hand, the processing module106may retrieve the suggestion information303from related forum in the social network database304according to the keywords in the composite merchandise recommendation information111such that the participants can take the suggestion information303into consideration. Subsequently, the participants can edit the composite merchandise recommendation information111by transmitting the editing information301mentioned above.

In an embodiment, the processing module106receives application information305from the remote non-participant hosts300and302that do not correspond to the group of participants through the data transmission module104after the participants confirm the composite merchandise recommendation information111. The users that are not in the group of participants are allowed to purchase the merchandises.

It is noted that the number of the remote non-participant hosts is merely an example. In other embodiments, the number of the remote non-participant hosts can be adjusted according to the practical condition. Further, the social network database is not limited to the database included in the merchandise recommendation system1. In some embodiments, the suggestion information303can be retrieved from external social network databases.

FIG. 4is a block diagram of the merchandise recommendation system1in an embodiment of the present invention. Similar to the merchandise recommendation system1illustrated inFIG. 1, the merchandise recommendation system1illustrated inFIG. 4includes a user database100, a merchandise database102, a data transmission module104, a processing module106and a memory108.

In the present embodiment, the processing module106retrieves corresponding supplier information401from a supplier database400included in the merchandise recommendation system1according to the composite merchandise recommendation information111. The processing module106further transmits the composite merchandise recommendation information111to corresponding supplier hosts402and404through the data transmission module104according to the corresponding supplier information401. The processing module106further receives competitive bidding information403from the corresponding supplier hosts402and404through the data transmission module104and selects a matched supplier according to the competitive bidding information403and the corresponding user information107.

For example, the processing module106retrieves the corresponding supplier information401of the suppliers that is able to provide the merchandises such as, but not limited to travel agencies or private tour guides according to the sightseeing spot information or the boarding and lodging information in the composite merchandise recommendation information111. The processing module106transmits the composite merchandise recommendation information111to the corresponding supplier hosts402and404of theses suppliers and selects the matched supplier according to the competitive bidding information. In different embodiments, the matched supplier can be selected according to such as, but not limited to the quality or the cost of the merchandises.

It is noted that the number of the corresponding supplier hosts can be different depending on the practical condition and is not limited to the embodiment illustrated inFIG. 4.

Accordingly, the merchandise recommendation system1not only generates the composite merchandise recommendation information111to match the needs of the participants, also provides a supplier-selecting mechanism. The efficiency and accuracy of the recommendation is further increased.

FIG. 5is a flow chart of a merchandise recommendation method500in an embodiment of the present invention. The merchandise recommendation method500can be used in the merchandise recommendation system1depicted inFIG. 1. More specifically, the merchandise recommendation method500is implemented by using a computer program to control the modules in the merchandise recommendation system1. The computer program can be stored in a non-transitory computer readable medium such as a ROM (read-only memory), a flash memory, a floppy disc, a hard disc, an optical disc, a flash disc, a tape, an database accessible from a network, or any storage medium with the same functionality that can be contemplated by persons of ordinary skill in the art to which this invention pertains.

The merchandise recommendation method500comprises the steps outlined below. (The steps are not recited in the sequence in which the steps are performed. That is, unless the sequence of the steps is expressly indicated, the sequence of the steps is interchangeable, and all or part of the steps may be simultaneously, partially simultaneously, or sequentially performed).

In step501, the processing module106receives participant information131related to a group of participants and a piece of target merchandise information133from a remote originator host130through the data transmission module104.

In step502, the processing module106retrieves a plurality of pieces of corresponding user information107from the user database100according to the participant information131.

In step503, the processing module106retrieves a plurality pieces of corresponding merchandise information109from the merchandise database102according to the target merchandise information133.

In step504, the processing module106analyzes social influence information included in the corresponding user information107and preference information related to the corresponding merchandise information109to generate an analysis result.

In step505, the processing module106generates composite merchandise recommendation information111according to the analysis result.

In some embodiments, the processing module106selectively receives the suggestion information303and the editing information301to edit the composite merchandise recommendation information111.

In step506, the processing module106transmits the composite merchandise recommendation information111to the corresponding supplier hosts402and404through the data transmission module104.

In step507, the processing module106receives competitive bidding information403from the corresponding supplier hosts402and404through the data transmission module104to select a matched supplier according to the competitive bidding information403and the corresponding user information107.

It is noted that the merchandises related to traveling are used as examples in the embodiments mentioned above. In other embodiments, the merchandise recommendation system, the method and the non-transitory computer readable storage medium of the same for multiple users can be applied to other kinds of composite merchandises.