JP7283042B2 - Information processing device, learning device, information processing method, learning information production method, and program - Google Patents

Description

TECHNICAL FIELD The present invention relates to an information processing apparatus and the like for performing information processing related to product group contents such as electronic catalogs and web pages.

In the prior art, there is an electronic catalog editing device that can freely lay out based on an electronic catalog linked with a product sales system and can create a presentation sheet that maintains linkage with the product sales system. There was (for example, see patent document 1).

JP 2013-242634 A

However, in the conventional technology, it is difficult to propose product group contents that are selling well or that are estimated to sell well. Note that the product group content is, for example, an electronic catalog, a web page, or the like in which information on a plurality of products is posted.

The information processing apparatus of the first invention learns learning target information having one or more product attribute information having one or more attribute values of product information related to products and sales information related to sales of one or more products. a learning information storage unit for storing learning information obtained by learning; a receiving unit for receiving one or more target product information having one or more attribute values; and one or more target product information having one or more attribute values for learning. An information processing device that is applied to information and includes a sales information acquisition unit that acquires sales information and an output unit that outputs the sales information.

With such a configuration, it is possible to predict product sales information that is the effect of product group content, which is product information of one or more products.

In addition, in the information processing apparatus of the second invention, in contrast to the first invention, the one or more attribute values of the target product information are attribute values of the product itself, Image attribute value that is the attribute value of the image, Character string attribute value that is the attribute value of the product character string that is the character string related to the product that the product information has, Placement attribute value that is the attribute value of the placement of the product information, Periphery of the product information This is an information processing device that includes one or more attribute values among the attribute values of the product information arranged in the .

With such a configuration, it is possible to predict product sales information, which is the effect of the product group content.

In addition, in the information processing apparatus of the third invention, in contrast to the second invention, the reception unit has one or more attribute values of one or more types of the product itself attribute value and the image attribute value. further comprising an arrangement pattern information acquisition unit that receives target product information and acquires two or more arrangement pattern information, which is information of a layout pattern having one or more arrangement attribute values of each of the one or more target product information, and acquires sales information The unit acquires the sales information by applying the one or more attribute values received by the reception unit and the layout pattern information acquired by the layout pattern information acquisition unit to the learning information. a judgment unit for judging whether or not the sales information for each of the two or more arrangement pattern information acquired by the sales information acquisition unit satisfies a predetermined condition so that the sales situation is good. a configuration unit that arranges the two or more pieces of target product information according to the arrangement pattern information when the determination unit determines that the sales situation is good, and configures the product group content; or the product group content and sales information configured by the configuration unit.

With such a configuration, it is possible to propose the arrangement of product information that is estimated to have good sales conditions.

Further, in the information processing apparatus of the fourth invention, in contrast to the second invention, the reception unit receives one or two or more pieces of target product information having one or more attribute values, and the reception unit receives one or more the attribute value changing unit for changing a part of the attribute values of the sales information acquiring unit, the attribute value changed by the attribute value changing unit and one or more attribute values received by the receiving unit , the attribute value changing unit applies the unchanged attribute value to the learning information, acquires the sales information, and the sales information acquired by the sales information acquisition unit satisfies a predetermined condition. 1 or more pieces of target product information are arranged using a judgment unit that judges whether or not the sales situation is good, and the attribute value when the judgment unit judges that the sales situation is good, and the product group content is constructed. The output unit is an information processing device that outputs the product group content configured by the configuration unit, or the product group content configured by the configuration unit and the sales information.

With this configuration, it is possible to propose a change in the attribute value of product information that is estimated to have good sales conditions.

Further, in the information processing apparatus of the fifth invention, in contrast to the fourth invention, the attribute value changing unit selects the product itself attribute value, the image attribute value, It is an information processing device that changes any of the character string attribute values.

With this configuration, it is possible to propose a change in the attribute value of product information that is estimated to have good sales conditions.

Further, in the information processing apparatus of the sixth aspect of the present invention, in contrast to the fourth aspect, the attribute value changing unit is an information processing apparatus that changes the layout attribute value among the one or more attribute values received by the receiving unit. be.

With this configuration, it is possible to propose a change in arrangement of product information that is estimated to have good sales conditions.

Further, the information processing device of the seventh invention is a learning device that constitutes learning information used by the information processing devices of the first to sixth inventions, and has one or more attribute values of product information related to products. a learning information storage unit storing learning information obtained by learning learning target information having one or more product attribute information and sales information related to sales of one or more products; a receiving unit accepting learning target information; The learning device includes a learning unit that learns target information by a machine learning algorithm, acquires learning information, and stores the learning information in a learning information storage unit.

With such a configuration, learning information can be easily obtained.

According to the information processing apparatus of the present invention, it is possible to propose product group contents in which product information of one or more products is posted.

A diagram showing a conceptual diagram of an information system A according to Embodiment 1 Block diagram of the same information system A Flowchart for explaining an operation example of the information processing device 1 Flowchart for explaining an example of same product group content acquisition processing Flowchart for explaining an example of same pattern information acquisition processing Flowchart explaining an operation example of the terminal device 2 Diagram showing same attribute value condition management table Diagram showing the same layout information management table Diagram showing the product information management table Diagram showing the product information management table A diagram showing an example of the web page of the same automobile catalog Figure showing an example of sales performance of the same car Diagram showing same attribute value management table A diagram showing an example of the web page of the same automobile catalog Diagram showing the same output example Diagram showing the same output example FIG. 4 shows an example of a block diagram of the learning device 3; Overview of the computer system Block diagram of the same computer system

Hereinafter, embodiments of an information processing apparatus and the like will be described with reference to the drawings. It should be noted that, since components denoted by the same reference numerals in the embodiments perform similar operations, repetitive description may be omitted.

(Embodiment 1)

In this embodiment, an information system including an information processing device capable of predicting the sales status of products listed in product group content, which is one or more product information items such as electronic catalogs and web pages, will be described. More specifically, in the present embodiment, learning information obtained by learning learning target information having one or more item attribute information and sales information is stored, and one or more items having one or more attribute values are stored. An information system including an information processing device that receives target product information and outputs sales information will be described. It should be noted that the product here means an object to be sold, and is broadly interpreted to include services.

Further, in the present embodiment, an information system including an information processing device capable of proposing a change in the arrangement of product information, a change in the attribute value of product information, etc., which can be estimated to have good sales conditions or to improve sales conditions, will be described.

In addition, in the present embodiment, an information system including an information processing device capable of proposing product group content that is selling well or can be estimated to be selling well will be described.

FIG. 1 is a conceptual diagram of an information system A according to this embodiment. An information system A includes an information processing device 1 and one or more terminal devices 2 . The information processing device 1 is a so-called server device here. The information processing device 1 is, for example, a cloud server or an ASP server, but its type and installation location do not matter. The terminal device 2 is a mobile terminal such as a smart phone, a tablet terminal, a mobile phone, a so-called personal computer, or the like, and the type thereof does not matter.

FIG. 2 is a block diagram of the information system A according to this embodiment.

The information processing device 1 includes a storage unit 11 , a reception unit 12 , a processing unit 13 and an output unit 14 . The storage unit 11 includes a learning information storage unit 111 and an attribute value condition storage unit 112 . The processing unit 13 includes a learning unit 131 , an arrangement pattern information acquisition unit 132 , an attribute value change unit 133 , a sales information acquisition unit 134 , a determination unit 135 and a configuration unit 136 . The sales information acquisition unit 134 includes attribute value set acquisition means 1341 and sales information acquisition means 1342 .

The terminal device 2 includes a terminal storage section 21 , a terminal reception section 22 , a terminal processing section 23 , a terminal transmission section 24 , a terminal reception section 25 and a terminal output section 26 .

A storage unit 11 constituting the information processing apparatus 1 stores various kinds of information. Various types of information include, for example, learning information described later, attribute value conditions described later, one or more layout information, one or more target product information, or product group content having one or more target product information. etc. The target product information is product information to be processed by the information processing apparatus 1 .

Layout information is information for determining the layout of one or more items of product information. The layout information is, for example, a layout attribute value indicating the layout position of the product information (for example, the upper left coordinate value of the region), and a set of one or more attribute values of the product information that can be laid out in the region determined by the layout attribute value. is. Product information is information about products, and is content arranged in product group content such as electronic catalogs and web pages. The product group content may be information including one product information. The product group content may be content having the concept of pages, or may be content having no concept of pages.
The product information includes, for example, product images, product character string product animations, product sounds, and the like. A product image is an image of a product. The product character string is a character string that describes the product. A product video is a video explaining a product. A product voice is a voice that describes a product. One or more attribute values of the product information may be stored in association with the product information.

The attribute values of product information are, for example, product itself attribute values, image attribute values, character string attribute values, moving image attribute values, audio attribute values, layout attribute values, and the like. The product itself attribute value is an attribute value of the product itself, such as product color, product shape, product weight, product type, and product type. The image attribute value is the attribute value of the product image included in the product information, and includes, for example, the size of the product image, the color of the product image, the resolution of the product image, the brightness of the product image, and the shape of the product image. The color of the product image is, for example, the average value of the color components of the pixel values forming the product image. The brightness of the product image is, for example, the average value of the brightness of the pixels forming the product image. A character string attribute value is an attribute value of a character string that describes a product, such as font, character size, and length. A video attribute value is an attribute value of a product video included in product information, and includes, for example, one or more feature amounts of the product video. The feature amounts are, for example, the length of the product video, the resolution of the product video, information indicating whether or not the product video has subtitles, information indicating whether or not the product video has commercials, and the number of times the product video has been viewed. information indicating whether there are comments in the product video, information indicating whether the product video is divided, various feature amounts of other product videos, feature values of still images that make up the product video is. Note that there are various types of feature amounts for moving images and feature amounts for still images, and techniques for acquiring the feature amounts are well-known techniques. The audio attribute value is an attribute value of audio information included in product information, and includes, for example, one or more feature amounts of product audio. The features include, for example, the length of the product voice, the volume of the product voice, the quality of the product voice, the key of the product voice, the gender of the speaker of the product voice, information indicating whether the product voice has BGM, These are the insertion position, information indicating whether or not sound effects are present in the product sound, the sound effect insertion positions, and other sound feature amounts. It should be noted that there are various types of speech feature amounts, and techniques for acquiring feature amounts are well-known techniques. The layout attribute value is the attribute value of the layout of product information, and includes an absolute layout attribute value, an attribute value of product information around the product information, and the like. The absolute layout attribute value is an attribute value relating to the layout of the product information itself, and includes, for example, the position within the page [eg, top, middle, bottom, left, center, right]), coordinate values, page number, and the like. The product information around the product information is, for example, product information adjacent to the product information and product information arranged on the same page as the product information. Also, the sales information is information on sales of products. Also, the sales information is, for example, the number of sales, the total sales amount, and the like. The sales information is preferably the total sales amount or the total number of sales of two or more products, but may be the sales amount or the number of sales of each of two or more products.

The learning information storage unit 111 stores learning information.

The learning information is, for example, information acquired by learning by the learning unit 131 . Details of the learning unit 131 will be described later. The learning information is, for example, information obtained by learning the learning target information. Also, the learning target information has one or more items of product attribute information and sales information. Product attribute information has one or more attribute values corresponding to product information. The one or more attribute values corresponding to the product information may be one or more attribute values possessed by the product information, one or more attribute values linked to the product information, or one or more that can be obtained from the product information. attribute value is also acceptable. The learning target information may be information having product group content and sales information. The learning target information may be information having two or more product attribute information and sales information acquired from the product group content.

The learning information may be information having a plurality of sets of one or more attribute values of each item information and sales information.

The attribute value condition storage unit 112 stores one or more attribute value conditions regarding conditions that attribute values can take. The attribute value condition has an attribute identifier that identifies the attribute value and an attribute value change condition.

Attribute identifiers are, for example, attribute names and IDs. Attribute names include, for example, "color" indicating the color of the product, "shape" indicating the shape of the product, "weight" indicating the weight of the product, "type" indicating the type of product, and "size" indicating the size of the product image. "Image size", "Image color" indicating the color of the product image, "Resolution" indicating the resolution of the product image, "Brightness" indicating the brightness of the product image, "Image shape" indicating the shape of the product image, Describe the product "Font" indicating the font of the character string, "Character size", "Character string length" indicating the length of the character string describing the product, "Video time" indicating the playback time of the video explaining the product, Description of the product "Audio type" indicating the type of audio to be played, "Page position" indicating the position within the page, "Coordinate value" indicating the coordinate value within the page, "Page number" indicating the page number where the product information is placed, "Surrounding image size" indicating the size of the product image of the surrounding product information, "Surrounding image resolution" indicating the resolution of the product image of the surrounding product information, "Surrounding product character size" indicating the character size of the surrounding product information , “Peripheral product character string length” indicating the length of the character string of the peripheral product information, and the like. The "peripheral image size" is, for example, the "upper product image size" that is the size of the adjacent upper product image, the "horizontal product image size" that is the size of the adjacent horizontal product image, and the adjacent lower product image. "lower product image size", which is the size of the product. The "peripheral image resolution" is, for example, the "upper product image resolution" that is the resolution of the adjacent upper product image, the "horizontal product image resolution" that is the resolution of the adjacent horizontal product image, and the adjacent lower product image. "lower product image resolution", etc., which is the resolution of the The "peripheral product character size" is, for example, the "upper product character size", which is the character size of the adjacent upper product character string, the "horizontal product character size", which is the character size of the adjacent horizontal product character string, The character size of the character string of the lower product is "lower product character size". The "peripheral product character string length" is, for example, the "upper product character string length" that is the length of the adjacent upper product character string, and the "horizontal product character string length" that is the length of the adjacent horizontal product character string. , "lower product character string length", which is the length of the adjacent lower product character string, and the like.

The attribute value change condition is, for example, a set of candidate information that the attribute value can take and information on the range of values that the attribute value can take. A set of information on candidates that can be attribute values is, for example, "font = Gothic, Mincho, ...", "character size = 10pt, 12pt, 14pt, ...", "page position = ( 1st, left), (1st, right), (2nd, left), (3rd, right), (3rd, left), (3rd, right), . Information on the range of values that the attribute value can take is, for example, "(x1, y1) <= image size <= (x2, y2) (x1, x2 are widths, y1, y2 are heights)", "1 <= page number <= 10" and "10 pt <= peripheral product character size <= 16 pt".

The receiving unit 12 receives one or more pieces of target product information having one or more attribute values. The target product information is usually product information that constitutes product group content to be output. The target product information may be, for example, one or more attribute values of product information that constitutes product group content to be output.

Here, the one or more attribute values are preferably one or more attribute values of product attribute values and image attribute values.

The receiving unit 12 may receive, for example, a learning instruction, a proposal instruction, and a sales forecast instruction.

The learning instruction has learning target information. The learning target information is information to be learned. The learning target information is information used by the sales information acquisition unit 134 to acquire sales information. The learning target information has product attribute information of one or more products and sales information. Product attribute information has one or more attribute values of product information.

The proposal instruction is an instruction to propose product group content. The suggestion instruction may be an instruction to output product group content that is estimated to have a favorable sales situation, or an instruction to output product group content that is estimated to improve the sales situation. A proposal instruction has, for example, one or more target product information. The suggestion instruction has, for example, product group content. When the proposal instruction includes product group content, for example, the reception unit 12 acquires one or more attribute values of one or more product information items included in the product group content. Such one or more attribute values are target product information.

The sales forecast instruction is an instruction to output a sales forecast. The sales forecast instruction has, for example, one or more target product information. The sales forecast instruction has product group content, for example. When the sales prediction instruction includes product group content, for example, the receiving unit 12 acquires one or more attribute values of one or more product information items included in the product group content. Such one or more attribute values are target product information.

Here, reception usually means reception from the terminal device 2, but reception of information input from an input device such as a keyboard, mouse, or touch panel, and reading from a recording medium such as an optical disk, a magnetic disk, or a semiconductor memory. It is a concept that includes the reception of information that has been received. Acceptance may be any process that can acquire target information or instructions.

If the reception is reception of information input from an input device, the input means may be anything such as a touch panel, a keyboard, a mouse, or a menu screen. In such a case, the reception unit 12 can be realized by a device driver for input means such as a touch panel or a keyboard, control software for a menu screen, or the like.

The processing unit 13 performs various types of processing. The various types of processing are, for example, processing performed by the learning unit 131, the arrangement pattern information acquisition unit 132, the attribute value change unit 133, the sales information acquisition unit 134, the determination unit 135, and the configuration unit 136.

The learning unit 131 learns the learning target information by a machine learning algorithm and acquires learning information. Here, machine learning is, for example, SVR, deep learning, decision tree, random forest, SVM, and the like. However, any machine learning algorithm is acceptable.

The learning target information has one or more item attribute information and sales information. Product attribute information has one or more attribute values of product information. Sales information is usually information on sales of one or more products corresponding to one or more product attribute information. The sales information possessed by the learning target information is preferably information sold using product group content containing one or more product information corresponding to one or more product attribute information possessed by the learning target information. .

The learning target information may be product group content and sales information. In such a case, the learning unit 131 acquires one or more product attribute information from the product group content. Then, the learning unit 131 learns the obtained one or more pieces of product attribute information and the sales information included in the learning target information using a machine learning algorithm, and obtains learning information.

The learning information may be information for obtaining sales information when applying one or more attribute values of a product.

Note that the processing of the learning unit 131 is a well-known technology, and therefore detailed description thereof will be omitted. Also, the learning information may be, for example, information having a plurality of sets of one or more product attribute information and sales information. Also, the learning information may be, for example, a plurality of pieces of correspondence information that associate one or more items of product attribute information with sales information.

The layout pattern information acquisition unit 132 acquires two or more pieces of layout pattern information. The layout pattern information is information having one or more layout attribute values of one or more pieces of target product information, and is layout pattern information.

The arrangement pattern information acquisition unit 132 adds, for example, the arrangement order of two or more pieces of target product information received by the reception unit 12 to each piece of target product information. In such a case, the arrangement pattern information acquiring unit 132 may, for example, randomly add the arrangement order starting from 1 to the arbitrarily selected target product information. In addition, the arrangement pattern information acquisition unit 132 determines the arrangement order of each target product information (sorts the product information) based on, for example, a predetermined condition (condition using one or more attribute values), The arrangement order is added to each target product information. Further, the layout pattern information acquisition unit 132, for example, arranges one or more pieces of target product information according to two or more pieces of predetermined layout information, and obtains layout attribute values of one or more pieces of each piece of target product information. get. The arrangement pattern information is information for arranging one or more item information in the item group content. Once the arrangement pattern information is determined, the arrangement of one or more items of product information is usually determined.

The attribute value changing unit 133 changes a part of the one or more attribute values included in the one or more pieces of target product information received by the receiving unit 12 . It does not matter how the attribute value changing unit 133 changes the attribute value. However, it is preferable that the attribute value changing unit 133 changes the attribute value so as to match the attribute value condition. For example, if the attribute value condition is a set of information on candidates that the attribute value can take, the attribute value changing unit 133 selects one candidate from among the candidates that the attribute value can take, and is determined as the attribute value after change. Further, when the attribute value condition is, for example, information on the range of values that the attribute value can take, the attribute value changing unit 133, for example, randomly acquires one value from the range, and changes the value to Decide on an attribute value.

The attribute value changing unit 133 selects any one of the product itself attribute value, the image attribute value, and the character string attribute value among the one or more attribute values possessed by the one or two or more pieces of target product information received by the receiving unit 12. You can change it.

The attribute value changing unit 133 may change the layout attribute value among the one or more attribute values included in the one or more pieces of target product information received by the receiving unit 12 .

The sales information acquisition unit 134 acquires sales information by applying one or more attribute values of the one or more pieces of target product information received by the reception unit 12 to the learning information. It can be said that the sales information here is sales forecast information.

The process of applying one or more attribute values to the learning information is, for example, a process using a machine learning algorithm. Further, the process of applying one or more attribute values to the learned information includes, for example, selecting one or more attribute values closest to the one or more attribute values from the learned information and acquiring the sales information included in the selected learned information. processing.

The process of applying one or more attribute values to the learning information is, for example, one or more attribute values closest to the one or more attribute values of each of the one or two or more target product information received by the receiving unit 12, from the learning information. This is a process of selecting and acquiring sales information paired with the selected one or more attribute values from learning information.

The sales information acquisition unit 134 acquires sales information by applying target product information to learning information using, for example, a machine learning algorithm. Note that machine learning is, for example, SVR, deep learning, decision tree, random forest, SVM, and the like. Moreover, it is preferable that the two or more target product information received by the receiving unit 12 here does not include sales information.

The sales information acquisition unit 134 acquires sales information by applying the one or more attribute values received by the reception unit 12 and the layout pattern information acquired by the layout pattern information acquisition unit 132 to learning information. It is preferable to carry out for each arrangement pattern information described above. The two or more pieces of layout pattern information are pieces of layout pattern information acquired by the layout pattern information acquisition unit 132 .

The sales information acquiring unit 134 converts the attribute value changed by the attribute value changing unit 133 and the attribute value not changed by the attribute value changing unit 133 among the one or more attribute values accepted by the accepting unit 12 into learning information. It is preferable to apply and obtain sales information.

The sales information acquiring unit 134 selects the attribute value changed by the attribute value changing unit 133 and one or more attribute values received by the receiving unit 12 for each combination of attribute value changes made by the attribute value changing unit 133. It is preferable to apply the attribute values that have not been changed by the changing unit 133 to the learning information to acquire the sales information.

The attribute value set acquisition unit 1341 acquires one or more attribute value sets. The attribute value set may be a set of attribute values acquired only from one or more attribute values included in one or more pieces of target product information received by the receiving unit 12 . Further, the attribute value set is obtained from the one or more attribute values acquired by the arrangement pattern information acquiring unit 132 in addition to the one or more attribute values possessed by the one or more pieces of target product information accepted by the accepting unit 12, A set of acquired attribute values may also be used. In addition, the attribute value set includes the attribute values that have not been changed by the attribute value changing unit 133 and the attribute value changing unit It may be a set of attribute values obtained from the attribute values changed by 133 . Further, the attribute value set includes the attribute values that have not been changed by the attribute value changing unit 133 among the one or more attribute values that the one or more pieces of target product information that the receiving unit 12 has received, and the attribute value changing unit 133 A set of attribute values acquired from one or more layout attribute values acquired by the layout pattern information acquisition unit 132 and the changed attribute values may be used. The structure of the attribute value set acquired by the attribute value set acquisition means 1341 and the structure of one or more attribute values, etc. possessed by one or two or more pieces of target product information received by the reception unit 12 may be the same or different. good.

The attribute value set acquisition means 1341 acquires possible values of attribute values for each of one or more attributes so as to satisfy attribute value change conditions corresponding to each attribute, and obtains possible values of the attribute values. It is preferable to obtain combinations of possible attribute values from the set of . A combination of attribute values may be called an attribute value set.

The sales information acquisition means 1342 applies the attribute value set acquired by the attribute value set acquisition means 1341 to learning information to acquire sales information. The sales information acquisition means 1342 applies the attribute value set acquired by the attribute value set acquisition means 1341 to learning information, for example, and acquires sales information by a machine learning algorithm. In addition, the sales information acquisition unit 1342 searches the learning information for one or more attribute values whose similarity to the attribute value set acquired by the attribute value set acquisition unit 1341 satisfies a predetermined condition. One or more pieces of sales information paired with the above attribute values are obtained from the learning information. In addition, the sales information acquisition means 1342, for example, searches the learning information for one or more attribute values that have the highest degree of similarity to the attribute value set acquired by the attribute value set acquisition means 1341, and pairs with the one or more attribute values. Obtain sales information that is different from learning information.

The determination unit 135 determines whether or not the sales information for each of the two or more pieces of arrangement pattern information acquired by the sales information acquisition unit 134 is so good that it satisfies a predetermined condition. The predetermined condition is, for example, that the sales information, which is the total sales amount, is equal to or greater than a threshold. Also, the predetermined condition is, for example, that the sales information, which is the total number of sales, is greater than or equal to a threshold. Also, the predetermined condition is, for example, that the sales situation is improved as compared with the received sales information. Such is, for example, that the total sales obtained are greater than the total sales received, or that the total sales obtained are greater than the total sales received. The received total sales amount and the received total sales amount are usually information on the actual sales performance of the product group content to be improved.

The judgment unit 135 judges whether or not the sales information obtained by the sales information obtaining unit 134 satisfies a predetermined condition so that the sales situation is good.

The configuration unit 136 configures product group content by arranging one or more pieces of target product information according to, for example, arrangement pattern information when the determination unit 135 determines that the sales situation is good.

The configuration unit 136 arranges one or more pieces of target product information and configures product group content, for example, using attribute values when the determination unit 135 determines that the sales situation is good.

When two or more pieces of sales information are acquired, the configuration unit 136 may select sales information that satisfies a predetermined condition. Then, using the attribute value corresponding to the selected sales information, the configuration unit 136 arranges one or more pieces of target product information to configure product group content.

The output unit 14 outputs the sales information acquired by the sales information acquisition unit 134, for example. The output unit 14 outputs the product group content configured by the configuration unit 136, for example. Also, the output unit 14 outputs, for example, the product group content configured by the configuration unit 136 and the sales information acquired by the sales information acquisition unit 134 . The product group content output by the output unit 14 may be information on one product.

Here, the output usually means transmission to an external device (usually, the terminal device 2), but display on a display, projection using a projector, printing on a printer, sound output, storage on a recording medium , and the delivery of processing results to other processors or other programs.

In addition, when the output is delivery of sales information, it is delivery of sales information to the determination part 135, for example.

Various kinds of information are stored in the terminal storage unit 21 that constitutes the terminal device 2 . Various information is, for example, a user identifier that identifies a user. Various information is, for example, information received by the terminal reception unit 25 . Note that the user identifier may be information for identifying the terminal device 2 .

The terminal reception unit 22 receives various instructions, information, and the like. Various instructions and information are, for example, learning instructions, proposal instructions, sales forecast instructions, learning target information, one or more target product information, and the like. Here, reception means reception of information input from input devices such as keyboards, mice, and touch panels, reception of information transmitted via wired or wireless communication lines, and recording of information on optical discs, magnetic discs, semiconductor memories, etc. This is a concept that includes acceptance of information read from a medium.

Any means such as a touch panel, keyboard, mouse, or menu screen may be used as input means for various instructions and information. The terminal reception unit 22 can be realized by a device driver for input means such as a touch panel or a keyboard, control software for a menu screen, or the like.

The various types of processing performed by the terminal processing unit 23 are, for example, processing for configuring information received by the terminal receiving unit 25 into data to be displayed. The various types of processing are, for example, processing for configuring an instruction or the like received by the terminal reception unit 22 into an instruction or the like to transmit.

The terminal transmission unit 24 transmits various instructions, information, and the like to the information processing device 1 . The various instructions and information are, for example, instructions configured by the terminal processing unit 23 and instructions and information received by the terminal reception unit 22 .

The terminal reception unit 25 receives various information from the information processing device 1 . Various types of information are, for example, sales information and product group content.

The terminal output unit 26 acquires various kinds of information. The various types of information are, for example, information received by the terminal reception unit 22, information received by the terminal reception unit 25, and information configured by the terminal processing unit 23. FIG. Various types of information are, for example, sales information and product group content.

Here, output means display on a display, projection using a projector, printing on a printer, sound output, transmission to an external device, storage in a recording medium, transfer to another processing device or other program, etc. This is a concept that includes delivery of processing results.

The storage unit 11, the learning information storage unit 111, the attribute value condition storage unit 112, and the terminal storage unit 21 are preferably non-volatile recording media, but can also be realized with volatile recording media.

It does not matter how the information is stored in the storage unit 11 or the like. For example, information may be stored in the storage unit 11 or the like via a recording medium, or information transmitted via a communication line or the like may be stored in the storage unit 11 or the like. Alternatively, information input via an input device may be stored in the storage unit 11 or the like.

The processing unit 13, the learning unit 131, the arrangement pattern information acquisition unit 132, the attribute value change unit 133, the sales information acquisition unit 134, the determination unit 135, the configuration unit 136, and the terminal processing unit 23 are usually implemented by an MPU, memory, or the like. can be The processing procedure of the processing unit 13 and the like is normally realized by software, and the software is recorded in a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

The output unit 14 and the terminal transmission unit 24 are usually realized by wireless or wired communication means, but may be realized by broadcasting means.

The output unit 14 may be realized by driver software of an output device, or driver software of an output device and an output device.

The terminal output unit 26 may or may not include an output device such as a display or speaker. The terminal output unit 26 can be realized by output device driver software, or by output device driver software and an output device.

Next, the operation of the information system A will be explained. First, an operation example of the information processing apparatus 1 will be described with reference to the flowchart of FIG.

(Step S301) The reception unit 12 determines whether or not a study instruction has been received. If the learning instruction is accepted, the process goes to step S302, and if the learning instruction is not accepted, the process goes to step S304.

(Step S302) The learning unit 131 acquires learning target information included in the learning instruction accepted in step S301. Then, the learning unit 131 acquires one or more attribute values of two or more items of product information included in the learning target information. The learning unit 131 also acquires sales information included in the learning target information. Then, the learning unit 131 pairs the acquired two or more attribute values and the sales information, performs machine learning processing, and acquires learning information. Sales information is obtained by applying two or more attribute values to the learned information.

Note that the learning unit 131 may acquire the product group content and sales information included in the learning instruction received in step S301. In such a case, the learning unit 131 acquires one or more attribute values of one or more product information of the product group content. Then, the learning unit 131 pairs one or more attribute values of one or more pieces of product information with the sales information, performs machine learning processing, and acquires learning information. Sales information is obtained by applying one or more attribute values to the learned information.

(Step S<b>303 ) The learning unit 131 accumulates the learning information acquired in step S<b>302 in the learning information storage unit 111 . Return to step S301.

(Step S<b>304 ) The reception unit 12 determines whether or not a proposal instruction has been received from the terminal device 2 . When the proposal instruction is received, the process goes to step S305, and when the proposal instruction is not received, the process goes to step S307.

(Step S305) The processing unit 13 acquires product group content using one or more target product information included in the proposal instruction. Such product group content acquisition processing will be described with reference to the flowchart of FIG.

(Step S<b>306 ) The output unit 14 transmits the product group content acquired in step S<b>305 to the terminal device 2 . Return to step S301.

(Step S<b>307 ) The reception unit 12 determines whether or not a sales forecast instruction has been received from the terminal device 2 . When the sales forecast instruction is received, the process goes to step S308, and when the sales forecast instruction is not received, the process returns to step S301.

(Step S308) The sales information acquisition unit 134 acquires one or more target product information contained in the sales forecast instruction received in step S307. If the sales prediction instruction includes product group content, the sales information acquisition unit 134 acquires target product information corresponding to one or more product information items from the product group content.

(Step S309) The sales information acquisition unit 134 acquires sales information by applying the one or more target product information acquired in step S308 to the learning information. Note that applying one or more pieces of target product information to learning information means, for example, applying one or more attribute values of each piece of one or more pieces of target product information to learning information.

(Step S<b>310 ) The output unit 14 transmits the sales information acquired in step S<b>309 to the terminal device 2 . Return to step S301.

Note that in the flowchart of FIG. 3, the process ends when the power is turned off or an interrupt for ending the process occurs.

Next, an example of product group content acquisition processing in step S305 will be described using the flowchart of FIG.

(Step S401) The arrangement pattern information acquisition unit 132 and the like acquire pattern information. Such pattern information acquisition processing will be described with reference to the flowchart of FIG. Note that the pattern information is usually a combination of two or more attribute values. It can be said that pattern information is a set of two or more attribute values. Also, the pattern information acquisition process acquires a set of two or more attribute values. It should be noted that at least a part of the attribute values of the sets of two or more attribute values are different from each other. Also, it may be considered that the pattern information may be one attribute value.

(Step S402) The sales information acquisition unit 134 substitutes 1 for the counter i.

(Step S403) The sales information acquisition unit 134 attempts to acquire the i-th attribute value combination from the set of attribute values acquired in step S401. Note that the i-th combination of attribute values is a set of i-th attribute values. Also, it may be considered that a single attribute value may suffice as a combination of attribute values.

(Step S404) The sales information acquiring unit 134 proceeds to step S405 if the i-th combination of attribute values has been acquired, and proceeds to step S407 if not.

(Step S405) The sales information acquisition unit 134 applies the i-th combination of attribute values to the learning information in the learning information storage unit 111 to acquire sales information. Then, the sales information acquiring unit 134 associates the acquired sales information with the combination of the i-th attribute values, and temporarily stores it in a buffer (not shown).

(Step S406) The sales information acquisition unit 134 increments the counter i by 1. Return to step S403.

(Step S407) The determination unit 135 determines sales information that satisfies a predetermined condition from among the one or more sales information acquired in step S405. Then, the determination unit 135 acquires a combination of attribute values corresponding to the determined one or more items of sales information from a buffer (not shown). The sales information that satisfies a predetermined condition is usually sales information that improves the sales situation as much as the predetermined condition is satisfied, or sales information that improves the sales situation as the predetermined condition is satisfied.

(Step S408) The configuration unit 136 substitutes 1 for the counter j.

(Step S409) The configuration unit 136 determines whether or not the j-th combination of attribute values exists among the combinations of attribute values acquired in step S407. If the j-th attribute value combination exists, go to step S410, and if the j-th attribute value combination does not exist, return to the higher-level processing.

(Step S410) The configuration unit 136 arranges two or more pieces of target product information according to the j-th combination of attribute values to configure product group content. The two or more pieces of target product information are usually information received by the reception unit 12, but may be information stored in the storage unit 11. FIG.

(Step S<b>411 ) The output unit 14 transmits the product group content configured in step S<b>410 to the terminal device 2 .

(Step S412) The configuration unit 136 increments the counter j by 1. Return to step S409.

Next, an example of pattern information acquisition processing in step S401 will be described using the flowchart of FIG.

(Step S501) The attribute value changing unit 133 substitutes 1 for the counter i.

(Step S502) The attribute value changing unit 133 determines whether or not the attribute value of the i-th type exists. If the attribute value of the i-th type exists, go to step S503, and if the attribute value of the i-th type does not exist, go to step S505. Note that the attribute value changing unit 133 determines whether the i-th type of attribute value exists based on whether the i-th attribute value condition or the i-th attribute identifier exists in the attribute value condition storage unit 112, for example. determine whether or not

(Step S503) The attribute value changing unit 133 acquires all possible values of the attribute value of the i-th type. If the attribute value change condition corresponding to the i-th type of attribute value is a set of information of candidates that the attribute value can take, the attribute value change unit 133 stores the attribute value that can be taken from the attribute value condition storage unit 112. Get all candidate information. Further, when the attribute value change condition corresponding to the attribute value of the i-th type is information on the range of possible values for the attribute value, the attribute value change unit 133, for example, stores the range from the attribute value condition storage unit 112 and obtain a set of two or more candidate information that satisfies the range. Note that the attribute value changing unit 133 may acquire a set of two or more candidate information that satisfies the range in any way. For example, the attribute value changing unit 133 may acquire a set of two or more candidate information while shifting a fixed value from the minimum value to the maximum value in the range, or , N (N is, for example, a fixed number) values may be obtained at random.

(Step S504) The attribute value changing unit 133 increments the counter i by 1. Return to step S502.

(Step S505) The attribute value changing unit 133 substitutes 1 for the counter j.

(Step S506) The attribute value changing unit 133 determines whether or not the j-th attribute value pattern exists. If the j-th attribute value pattern exists, go to step S507, and if the j-th attribute value pattern does not exist, return to the upper process.

Note that the attribute value changing unit 133 acquires all attribute value sets (attribute value patterns) from, for example, a set of two or more types of attribute value candidate information acquired in step S503. Then, the attribute value changing unit 133 determines whether or not the j-th attribute value pattern exists among the two or more attribute value patterns. Also, for example, there are two pieces of target product information (product information A and product information B), each of the target product information has attribute values of three attributes (attribute 1, attribute 2, and attribute 3), and attribute 1 is Attribute 2 can take either attribute value 11, attribute value 12, attribute 2 can take either attribute value 21, attribute value 22, or attribute 23, attribute 3 can take either attribute value 31, attribute value 32. do. In such a case, the attribute value changing unit 133 acquires 24 attribute value patterns. Also, there is one target product information (product information A), the target product information has attribute values of two attributes (attribute 1 and attribute 2), and attribute 1 is either attribute value 11 or attribute value 12 , and attribute 2 can take any of attribute value 21, attribute value 22, and attribute 23. In this case, the attribute value changing unit 133 acquires six attribute value patterns.

(Step S507) The arrangement pattern information acquisition unit 132 substitutes 1 for the counter k.

(Step S508) The arrangement pattern information acquisition unit 132 determines whether or not there is a k-th arrangement order combination based on the j-th attribute value pattern. If the k-th arrangement order combination exists, go to step S509, and if the k-th arrangement order combination does not exist, go to step S512.

(Step S509) The arrangement pattern information acquisition unit 132 acquires the k-th arrangement order combination based on the j-th attribute value pattern. Then, the arrangement pattern information acquiring unit 132 acquires one or more arrangement attribute values of each piece of product information using the k-th arrangement order combination. One or more layout attribute values of each target product information are layout pattern information. In addition, the combination of arrangement order is information indicating the arrangement order of one or more target product information (for example, the target product information to be arranged first from the upper left in the product group content, the target to be arranged second, etc.) product information, . Further, the attribute value changing unit 133, for example, arranges two or more pieces of target product information in order according to the information indicating the k-th arrangement order based on the j-th attribute value pattern, and arranges each of the two or more pieces of target product information. Get an attribute value. Also, the attribute value changing unit 133 arranges one piece of target product information according to the k-th arrangement pattern information based on the j-th attribute value pattern, for example.

(Step S510) The attribute value changing unit 133 acquires a combination of attribute values from the j-th attribute value pattern and the layout pattern information acquired in step S509, and temporarily stores them in a buffer (not shown).

(Step S511) The layout pattern information acquisition unit 132 increments the counter k by 1. Return to step S508.

(Step S512) The attribute value changing unit 133 increments the counter j by 1. Return to step S506.

Next, an operation example of the terminal device 2 will be described using the flowchart of FIG.

(Step S601) The terminal reception unit 22 determines whether or not a study instruction has been received. If the learning instruction is accepted, the process goes to step S602, and if the learning instruction is not accepted, the process goes to step S604.

(Step S602) The terminal processing unit 23 composes a learning instruction to be transmitted. Note that the learning instruction to be transmitted usually includes two or more pieces of learning target information.

(Step S603) The terminal transmission unit 24 transmits the study instruction configured in step S602 to the information processing device 1. FIG. Return to step S601.

(Step S604) The terminal reception unit 22 determines whether or not a proposal instruction has been received. If the proposal instruction is received, the process goes to step S605, and if the proposal instruction is not received, the process goes to step S610.

(Step S605) The terminal processing unit 23 composes a proposal instruction to be transmitted. Note that the proposal instruction to be transmitted includes two or more pieces of target product information or product group content.

(Step S<b>606 ) The terminal transmission unit 24 transmits the proposal instruction configured in step S<b>605 to the information processing device 1 .

(Step S<b>607 ) The terminal reception unit 25 determines whether or not one or more product group contents have been received from the information processing device 1 . If the product group content has been received, the process goes to step S608, and if the product group content has not been received, the process goes to step S607.

(Step S608) The terminal processing unit 23 configures product group content to be output.

(Step S609) The terminal output unit 26 outputs the product group content configured in step S608. Return to step S601.

(Step S610) The terminal reception unit 22 determines whether or not a sales forecast instruction has been received. If the sales forecast instruction is accepted, the process goes to step S611, and if the sales forecast instruction is not accepted, the process returns to step S601.

(Step S611) The terminal processing unit 23 composes a sales forecast instruction to be transmitted. The sales forecast instruction to be transmitted includes two or more target product information or product group contents.

(Step S<b>612 ) The terminal transmission unit 24 transmits the sales forecast instruction configured in step S<b>611 to the information processing device 1 .

(Step S<b>613 ) The terminal reception unit 25 determines whether sales information has been received from the information processing device 1 . If the sales information has been received, the process goes to step S614, and if the sales information has not been received, the process goes to step S613.

(Step S614) The terminal processing unit 23 composes sales information to be output.

(Step S615) The terminal output unit 26 outputs the sales information configured in step S614. Return to step S601.

Note that in the flowchart of FIG. 6, the process ends when the power is turned off or an interrupt for ending the process occurs.

A specific operation of the information system A in this embodiment will be described below. A conceptual diagram of the information system A is shown in FIG.

Currently, the attribute value condition management table shown in FIG. 7 is stored in the attribute value condition storage unit 112 . The attribute value condition management table is a table for managing attribute value change conditions for each attribute. The attribute value change condition is information indicating possible attribute values. The attribute value condition management table has records having "ID", "attribute identifier", "attribute type", and "attribute value change condition" as many as the number of changeable attributes. "ID" is information for identifying a record. "attribute identifier" is here the attribute name. "Attribute type" indicates the type of attribute.

The storage unit 11 also stores a layout information management table shown in FIG. The layout information management table has a plurality of records having "ID", "layout identifier" and "layout information". "ID" is information for identifying a record. A "layout identifier" is information for identifying layout information, and is a layout information name here. The "layout information", which expresses a layout diagram for arranging the elements constituting the product information, has relative coordinate information for arranging the elements constituting the product information. Note that "ID" may be considered as a layout identifier.

The storage unit 11 also stores a product information management table shown in FIG. The storage unit 11 also stores a product information management table shown in FIG. The merchandise information management table manages two or more pieces of merchandise information. The merchandise information management table has "ID", "merchandise image", "merchandise itself attribute value", "merchandise name", and "merchandise description". "ID" is the ID of product information. The "item itself attribute value" has "price", "color", and the like here. "Product name" is the name of the product. "Item description" is a character string describing the item.

Under such circumstances, the following four specific examples will be described. Specific example 1 is a learning process by the learning unit 131 . A specific example 2 is sales prediction processing using learning information. A specific example 3 is a process of changing the product group content so as to improve the sales situation. Concrete example 4 is processing for creating product group content so as to obtain favorable sales results.
(Specific example 1)

In specific example 1, learning processing by the learning unit 131 will be described.

First, the user of the terminal device 2 inputs into the terminal device 2 a learning instruction including the electronic data of the web page of the automobile catalog shown in FIG. I did. The sales record of automobiles is an example of sales information, and includes the number of sales of each automobile, the total sales of each automobile, the total sales of all automobiles, and the total sales of all automobiles. "ID" in FIG. 12 is a product identifier.

Next, the terminal reception unit 22 receives a study instruction. The terminal processing unit 23 composes a learning instruction to be transmitted corresponding to the received learning instruction. Then, the terminal transmission unit 24 transmits the learning instruction to the information processing device 1 .

Next, the reception unit 12 of the information processing device 1 receives a study instruction from the terminal device 2 . This learning instruction includes the electronic data of the web page shown in FIG. 11 (the URL of the web page may be used) and the sales information shown in FIG. Also, the electronic data of the web page has two or more pieces of target product information. Here, the target product information is product information of each automobile.

Next, the reception unit 12 acquires the attribute value of each item of target product information from the electronic data of the web page in FIG. 11 . Specifically, the reception unit 12 acquires, for example, the product itself attribute values “price=2,500,000 yen” and “color=black” of the automobile with “ID=C1”. Further, _the reception unit 12, for example, analyzes _the product image of “ID=C1” included in the electronic data of the web page of FIG. Rectangle” etc. For example, the reception unit 12 acquires “font=Mincho”, “character size=11pt”, etc. from the character string “ID=C1” included in the electronic data of the web page of FIG. 11 . For example, the reception unit 12 analyzes the web page of FIG. 11, acquires information about the arrangement of each object on the web page, and obtains information about the layout of each object on the web page. Arrangement order=1” or the like is obtained. The reception unit 12 obtains the attribute value management table shown in FIG. 13 from the attribute values. It can be said that the acquisition of the attribute value is the reception of the attribute value.

Next, the learning unit 131 acquires one or more attribute values (attribute value management table in FIG. 13) acquired by the reception unit 12 . In addition, the learning unit 131 acquires the total number of vehicles sold and the total sales amount of all vehicles from the vehicle sales record of FIG. 12 received by the reception unit 12 . Here, it is assumed that the learning unit 131 acquires two types of sales information, the total number of units sold and the total sales amount. Then, the learning unit 131 associates one or more attribute values (attribute value management table in FIG. 13) with two types of sales information, and accumulates them in the storage unit 11 or a buffer (not shown). A set of one or more attribute values (attribute value management table in FIG. 13) and sales information is learning target information. Further, the learning target information is a vector connecting two or more vectors corresponding to each product information and sales information. That is, the learning target information is, for example, ((2.5 million yen, 1,0,0,...,1,0,1,0,...,0,1,...,2,1,... ...) (3 million yen, 0, 0, 1, ..., 1, 0, 1, 0, ..., 0, 1, ..., 2, 2, ...) (2.1 million yen , 0, 1, 0, ..., 1, 0, 1, 0, ..., 0, 1, ..., 2, 3, ...) ... 5483 units, 1, 425, 580 million yen). Note that the parentheses between product information in the learning target information may be omitted. Needless to say, the learning unit 131 may learn the number of units sold and the amount of sales of each car in the actual car sales shown in FIG.

It is assumed that the above processing has been performed on a large number of electronic data and sales information on other web pages, and a large amount of learning target information has been accumulated.

Next, the learning unit 131 learns a large amount of accumulated learning target information using a machine learning algorithm, acquires learning information, and stores it in the learning information storage unit 111 .

As described above, the learning information is obtained from which sales information is acquired when two or more pieces of target product information are applied.
(Specific example 2)

In Specific Example 2, processing for performing sales prediction processing using the learning information accumulated in Specific Example 1 will be described.

First, the user of the terminal device 2 wants to predict the sales based on the automobile catalog shown in FIG. do.

Next, the terminal reception unit 22 receives a sales forecast instruction. The terminal processing unit 23 composes a sales forecast instruction to be transmitted in accordance with the received sales forecast instruction. Then, the terminal transmission unit 24 transmits the sales forecast instruction to the information processing device 1 . The sales forecast instruction has the URL of the web page of the automobile catalog shown in FIG.

Next, the reception unit 12 of the information processing device 1 receives the sales forecast instruction from the terminal device 2 .

Next, the reception unit 12 acquires the URL included in the received sales forecast instruction. Next, the reception unit 12 acquires the web page of the automobile catalog corresponding to the URL. Next, the reception unit 12 acquires two or more pieces of target product information from the web page.

Next, the sales information acquisition unit 134 acquires a set of attribute values from each of the two or more pieces of target product information. Note that the acquired set of attribute values has, for example, the structure shown in FIG. Also, the set of acquired attribute values is, for example, a vector ((2,300,000 yen, 0, 1, 0, ..., 1, 0, 1, 0, ..., 1, 0, ..., 1 , 1, ...) (2.8 million yen, 0, 0, 1, ..., 1, 0, 1, 0, ..., 1, 0, ..., 1, 2, ...) (2.1 million yen, 0, 1, 0, ..., 1, 0, 1, 0, ..., 1, 0, ..., 1, 3, ...)).

Next, the sales information acquisition unit 134 adapts the vector to the learning information in the storage unit 11 and acquires sales information by machine learning algorithm. This vector is a vector obtained by concatenating two or more vectors corresponding to each target product information. Here, it is assumed that the sales information acquisition unit 134 has obtained the total sales volume of "8210" and the total sales amount of "2,102,492".

Next, the output unit 14 transmits the acquired sales information (the total number of units sold “8210” and the total sales amount “2,102,492”) to the terminal device 2 .

Next, the terminal receiving section 25 receives the sales information from the information processing device 1 . Next, the terminal processing unit 23 configures sales information to be output. The terminal output unit 26 outputs the configured sales information. An example of such an output is shown in FIG.
(Specific example 3)

In specific example 3, the process of changing the product group content so as to improve the sales situation using the learning information accumulated in specific example 1 will be described.

Assume that the user has input a proposal instruction including the URL of the web page shown in FIG.

Next, the terminal reception unit 22 receives the proposal instruction. The terminal processing unit 23 composes a proposal instruction to be transmitted in accordance with the received proposal instruction. Then, the terminal transmission unit 24 transmits the proposal instruction to the information processing device 1 . The proposal instruction has the URL of the web page of the automobile catalog shown in FIG.

Next, the reception unit 12 of the information processing device 1 receives the proposal instruction from the terminal device 2 .

Next, the reception unit 12 acquires the URL included in the proposal instruction. Next, the reception unit 12 acquires the web page of the automobile catalog corresponding to the URL. Next, the reception unit 12 acquires two or more pieces of target product information from the web page.

Next, the attribute value changing unit 133 acquires one or more attribute values from two or more pieces of target product information. Such an attribute value acquisition method is possible by the above-described processing.

Next, the attribute value change unit 133 acquires possible values for each attribute value so as to satisfy the attribute value change information in the attribute value condition management table of FIG. Then, the attribute value changing unit 133 acquires two or more attribute value patterns.

Next, the layout pattern information acquisition unit 132 acquires two or more pieces of layout pattern information for each attribute value pattern acquired by the attribute value change unit 133 .

As described above, a plurality of attribute value sets (combinations of attribute values) have been obtained. Note that the attribute value set acquisition processing has been described with reference to the flowchart of FIG. 5, so a detailed description thereof will be omitted here.

Next, the sales information acquisition unit 134 applies each attribute value set to the learning information in the learning information storage unit 111 and acquires sales information in association with the attribute value set.

Next, the determination unit 135 determines sales information that satisfies a predetermined condition from each sales information associated with the attribute value set. Here, for example, it is assumed that the determination unit 135 selects the sales information with the largest total sales amount. Then, the determination unit 135 acquires an attribute value set corresponding to the selected sales information with the largest total sales amount.

Next, the configuration unit 136 determines the attribute values of the product information in FIG. 9 according to the acquired attribute value set, determines the arrangement of each element constituting the product information, and configures the product group content. In addition, in a situation where the attribute values of product information and the layout of each element constituting the product information are determined, the technology for configuring the product group content using the elements constituting the product information is a known technology. Detailed description is omitted.

Next, the output unit 14 transmits the configured product group content and the total sales amount (an example of sales information) to the terminal device 2 .

Next, the terminal reception unit 25 of the terminal device 2 receives the product group content and sales information from the information processing device 1 . Next, the terminal processing unit 23 configures product group content and sales information to be output. The terminal output unit 26 outputs the configured product group content and sales information. An example of such an output is shown in FIG.
(Specific example 4)

In specific example 4, processing for generating product group content so as to obtain good sales results using the learning information accumulated in specific example 1 will be described.

Assume that the user has entered a proposal instruction designating the product information DB shown in FIG. 10 to create a new electronic catalog for automobile sales using the product information DB shown in FIG.

Next, the terminal reception unit 22 receives the proposal instruction. The terminal processing unit 23 composes a proposal instruction to be transmitted in accordance with the received proposal instruction. Then, the terminal transmission unit 24 transmits the proposal instruction to the information processing device 1 . It should be noted that the proposal instruction has information of the product information DB shown in FIG.

Next, the reception unit 12 of the information processing device 1 receives the plan instruction from the terminal device 2 . Then, the reception unit 12 acquires two or more pieces of target product information included in the proposal instruction.

Next, the attribute value change unit 133 acquires possible values for each attribute value so as to satisfy the attribute value change information in the attribute value condition management table of FIG. Then, the attribute value changing unit 133 acquires two or more attribute value patterns.

Next, the layout pattern information acquisition unit 132 acquires two or more pieces of layout pattern information for each attribute value pattern acquired by the attribute value change unit 133 .

As described above, a plurality of attribute value sets (combinations of attribute values) have been acquired.

Next, the sales information acquisition unit 134 applies each attribute value set to the learning information in the learning information storage unit 111 and acquires sales information in association with the attribute value set.

Next, the determination unit 135 determines sales information that satisfies a predetermined condition from each sales information associated with the attribute value set. Here, for example, it is assumed that the determination unit 135 has selected sales information with the top three sales totals. Then, the determination unit 135 acquires an attribute value set corresponding to each of the selected three pieces of sales information.

Next, the configuration unit 136 configures three product group contents according to the three acquired attribute value sets.

Next, the output unit 14 transmits to the terminal device 2 three sets of the composed product group content and the total number of sales (an example of sales information).

Next, the terminal reception unit 25 of the terminal device 2 receives three sets of product group contents and sales information from the information processing device 1 . Next, the terminal processing unit 23 configures three sets of product group content and sales information to be output. The terminal output unit 26 outputs three sets of product group contents and sales information.

Next, the user checks three sets of product group contents and sales information, and selects, for example, one product group content. This selected product group content is the adopted product group content.

As described above, according to the present embodiment, it is possible to predict product sales information, which is the effect of the product group content.

Moreover, according to the present embodiment, it is possible to propose product group contents that are estimated to have good sales conditions. Note that the product group content may be information on one product as described above.

Further, according to the present embodiment, it is possible to propose a change in the attribute value of product information that is estimated to have good sales conditions. Note that the change of the attribute value of the product information may be the change of the attribute value of the product information of one product.

Furthermore, according to the present embodiment, it is possible to propose a change in the attribute value of product information that is estimated to improve the sales situation. Note that the change of the attribute value of the product information may be the change of the attribute value of the product information of one product.

Note that the learning process described above may be performed by a device independent of the information processing device. In this case, the learning device 3 comprises a storage unit 11 , a receiving unit 12 and a learning unit 131 . An example of a block diagram of such a learning device 3 is shown in FIG. The learning device 3 stores learning information obtained by learning learning target information having two or more product attribute information having one or more attribute values of product information related to products and sales information related to sales of one or more products. A learning information storage unit 111, a receiving unit 12 that receives learning target information, and a learning unit that learns the learning target information by a machine learning algorithm, acquires learning information, and stores the learning information in the learning information storage unit 111. 131.

Also, the processing in the present embodiment may be realized by software. Then, this software may be distributed by software download or the like. Also, this software may be recorded on a recording medium such as a CD-ROM and distributed. Note that this also applies to other embodiments in this specification. The software that implements the information processing apparatus 1 according to the present embodiment is the following program. In other words, this program is learning information obtained by learning learning target information having, for example, one or more product attribute information having one or more attribute values of product information related to products and sales information related to sales of one or more products. a computer capable of accessing a recording medium having a learning information storage unit in which is stored a receiving unit that receives one or more target product information having one or more attribute values; It is a program for functioning as a sales information acquisition unit that acquires sales information by applying one or more attribute values possessed to the learning information, and as an output unit that outputs the sales information.

Further, the software that implements the learning device 3 is the following program. In other words, this program is, for example, a program for producing learning information used by the information processing apparatus 1, and a computer, one or two or more product attribute information having one or more attribute values of product information related to products, A reception unit that receives learning target information having sales information related to sales of one or more products, and a learning that learns the learning target information by a machine learning algorithm, acquires learning information, and stores the learning information in a recording medium. It is a program for functioning as a department.

Also, FIG. 18 shows the appearance of a computer that executes the programs described in this specification and realizes the information processing apparatus 1 and the like of the various embodiments described above. The embodiments described above may be implemented in computer hardware and computer programs running thereon. FIG. 18 is an overview diagram of this computer system 300, and FIG. 19 is a block diagram of the system 300. As shown in FIG.

In FIG. 18, computer system 300 includes computer 301 including a CD-ROM drive, keyboard 302 , mouse 303 and monitor 304 .

In FIG. 19, a computer 301 includes a CD-ROM drive 3012, an MPU 3013, a bus 3014 connected to the CD-ROM drive 3012, a ROM 3015 for storing programs such as a boot-up program, It includes a RAM 3016 connected and for temporarily storing application program instructions and providing temporary storage space, and a hard disk 3017 for storing application programs, system programs and data. Although not shown here, computer 301 may also include a network card that provides connection to a LAN.

A program that causes the computer system 300 to execute the functions of the information processing apparatus 1 of the embodiment described above may be stored in the CD-ROM 3101, inserted into the CD-ROM drive 3012, and further transferred to the hard disk 3017. . Alternatively, the program may be transmitted to computer 301 via a network (not shown) and stored in hard disk 3017 . Programs are loaded into RAM 3016 during execution. The program may be loaded directly from CD-ROM 3101 or network.

The program does not necessarily include an operating system (OS) or a third-party program that causes the computer 301 to execute the functions of the information processing apparatus 1 of the embodiment described above. A program need only contain those parts of instructions that call the appropriate functions (modules) in a controlled manner to produce the desired result. How the computer system 300 operates is well known and will not be described in detail.

In the above program, the step of transmitting information, the step of receiving information, etc. are performed by hardware. processing) are not included.

Also, the number of computers that execute the above programs may be singular or plural. That is, centralized processing may be performed, or distributed processing may be performed.

Further, in each of the above embodiments, it goes without saying that two or more communication means existing in one device may be physically realized by one medium.

Further, in each of the above embodiments, each process may be implemented by centralized processing by a single device, or may be implemented by distributed processing by a plurality of devices. For example, it goes without saying that the information processing apparatus 1 may operate stand-alone. In such a case, the receiving unit 12 receives, for example, instructions from the user. Also, the output unit 14 displays information on a display or the like, for example.

It goes without saying that the present invention is not limited to the above-described embodiments, and that various modifications are possible and are also included within the scope of the present invention.

INDUSTRIAL APPLICABILITY As described above, the information processing apparatus according to the present invention has the effect of being able to propose product group content in which information on a plurality of products is posted, and is useful as an information processing apparatus or the like.

1 information processing device 2 terminal device 3 learning device 11 storage unit 12 reception unit 13 processing unit 14 output unit 21 terminal storage unit 22 terminal reception unit 23 terminal processing unit 24 terminal transmission unit 25 terminal reception unit 26 terminal output unit 111 learning information storage Unit 112 Attribute value condition storage unit 131 Learning unit 132 Arrangement pattern information acquisition unit 133 Attribute value change unit 134 Sales information acquisition unit 135 Judgment unit 136 Configuration unit 1341 Attribute value set acquisition means 1342 Sales information acquisition means

Claims (5)

1 or 2 or more product attribute information having 1 or more attribute values of product information that is product information related to products and constitutes product group content that is an electronic catalog or web page; and sales information related to sales of one or more products. A learning information storage unit that stores learning information obtained by learning learning target information having
a reception unit that receives one or more target product information that is product information that has one or more attribute values and that constitutes product group content;
a sales information acquisition unit that acquires sales information by applying one or more attribute values of each of the one or more target product information to the learning information;
and an output unit that outputs the sales information,
The one or more attribute values of the product information and the one or more attribute values of the target product information are layout attribute values of the product information or the target product information in the product group content. including
The reception unit
Receiving one or more target product information having one or more attribute values of the product itself attribute value and image attribute value,
further comprising an arrangement pattern information acquisition unit that acquires two or more arrangement pattern information, which is arrangement pattern information having one or more arrangement attribute values of each of the one or two or more target product information,
The sales information acquisition unit
The one or more attribute values selected from the product itself attribute value and the image attribute value received by the receiving unit, and the one or more layout attribute values included in the layout pattern information obtained by the layout pattern information obtaining unit. Applying to learning information and acquiring sales information for each of the two or more arrangement pattern information,
a judging unit for judging whether or not the sales information for each of the two or more arrangement pattern information acquired by the sales information acquisition unit is so favorable that the sales situation is so favorable as to satisfy a predetermined condition;
a configuration unit that arranges the two or more pieces of target product information according to the arrangement pattern information when the determination unit determines that the sales situation is good, and configures product group content;
The output unit
outputting the product group content configured by the configuration unit, or the product group content configured by the configuration unit and the sales information;
The arrangement pattern information acquisition unit
According to two or more pieces of layout information for arranging the elements constituting the product information, one or more pieces of target product information are arranged for each of the layout information, and one or more pieces of arrangement attributes of each piece of object product information. An information processing device that acquires arrangement pattern information including values . One or more attribute values of the product information and one or more attribute values of the target product information are
2. The information processing apparatus according to claim 1, wherein attribute values of product information arranged around said product information in the product group content include one or more attribute values. One or more attribute values of the product information and one or more attribute values of the target product information are
The product itself attribute value that is the attribute value of the product itself, the image attribute value that is the attribute value of the product image that the product information has, and the character string attribute that is the attribute value of the product character string that is the character string related to the product that the product information has 3. The information processing apparatus according to claim 1, wherein the values include one or more attribute values. 1 or 2 or more product attribute information having 1 or more attribute values of product information that constitutes product group content, which is product information related to a product, which is an electronic catalog or web page, and sales information related to the sale of one or more products An information processing method realized by a learning information storage unit storing learning information obtained by learning learning object information having There is
a receiving step in which the receiving unit receives one or more target product information, which is product information having one or more attribute values and constitutes product group content;
a sales information acquisition step in which the sales information acquisition unit acquires sales information by applying one or more attribute values of the one or more target product information to the learned information;
The output unit comprises an output step of outputting the sales information,
The one or more attribute values of the product information and the one or more attribute values of the target product information are layout attribute values of the product information or the target product information in the product group content. including
In the receiving step,
Receiving one or more target product information having one or more attribute values of the product itself attribute value and image attribute value,
The arrangement pattern information acquisition unit further comprises an arrangement pattern information acquisition step of acquiring two or more pieces of arrangement pattern information that are arrangement pattern information having one or more arrangement attribute values for each of the one or more target product information. death,
In the sales information acquisition step,
The one or more attribute values selected from the product itself attribute value and the image attribute value received by the receiving unit, and the one or more layout attribute values included in the layout pattern information obtained by the layout pattern information obtaining unit. Applying to learning information and acquiring sales information for each of the two or more arrangement pattern information,
The judging unit judges whether or not the sales information for each of the two or more arrangement pattern information acquired in the sales information acquisition step is so good that the sales conditions satisfy a predetermined condition. a decision step;
a configuration step in which the configuration unit configures the product group content by arranging the two or more target product information according to the arrangement pattern information when it is determined in the determination step that the sales situation is good,
In the output step,
outputting the product group content configured in the configuration step, or the product group content configured in the configuration step and the sales information;
In the arrangement pattern information acquisition step,
According to two or more pieces of layout information for arranging the elements constituting the product information, one or two or more pieces of target product information are arranged for each layout information, and one or two or more pieces of arrangement attributes of each piece of target product information are arranged. An information processing method for obtaining arrangement pattern information including values . 1 or 2 or more product attribute information having 1 or more attribute values of product information that constitutes product group content, which is product information related to a product, which is an electronic catalog or web page, and sales information related to the sale of one or more products A computer that can access a recording medium that has a learning information storage unit that stores learning information that has been learned from learning target information that has
a reception unit that receives one or more target product information that is product information that has one or more attribute values and that constitutes product group content;
a sales information acquisition unit that acquires sales information by applying one or more attribute values of each of the one or more target product information to the learning information;
A program for functioning as an output unit that outputs the sales information,
The one or more attribute values of the product information and the one or more attribute values of the target product information are layout attribute values of the product information or the target product information in the product group content. including
The reception unit
Receiving one or more target product information having one or more attribute values of the product itself attribute value and image attribute value,
further comprising an arrangement pattern information acquisition unit that acquires two or more arrangement pattern information, which is arrangement pattern information having one or more arrangement attribute values of each of the one or two or more target product information,
The sales information acquisition unit
The one or more attribute values selected from the product itself attribute value and the image attribute value received by the receiving unit, and the one or more layout attribute values included in the layout pattern information obtained by the layout pattern information obtaining unit. Applying to learning information and acquiring sales information for each of the two or more arrangement pattern information,
a judging unit for judging whether or not the sales information for each of the two or more arrangement pattern information acquired by the sales information acquisition unit is so favorable that the sales situation is so favorable as to satisfy a predetermined condition;
a configuration unit that arranges the two or more pieces of target product information according to the arrangement pattern information when the determination unit determines that the sales situation is good, and configures product group content;
The output unit
outputting the product group content configured by the configuration unit, or the product group content configured by the configuration unit and the sales information;
The arrangement pattern information acquisition unit
According to two or more pieces of layout information for arranging the elements constituting the product information, one or more pieces of target product information are arranged for each of the layout information, and one or more pieces of arrangement attributes of each piece of object product information. A program for causing the computer to function as one that acquires arrangement pattern information including values .

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