WO2018220928A1 - 商品等情報生成装置、商品等情報生成プログラム、商品等情報生成システム、及び、商品等情報生成方法 - Google Patents
商品等情報生成装置、商品等情報生成プログラム、商品等情報生成システム、及び、商品等情報生成方法 Download PDFInfo
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- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
Definitions
- the present invention relates to a product etc. information generating device, a product etc. information generating program, a product etc. information generating system, and a product etc. information generating method for generating a recommended (recommended) text related to a product or service.
- JP 2009-116548 A Japanese Patent Laying-Open No. 2015-121897
- Patent Document 1 is a “catch copy” that emphasizes only the merits of products, and is not a logical reason for recommendation according to the circumstances of individual customers.
- Patent Document 2 is a sentence generation for future prediction, and does not generate a logical recommendation reason considering the actual situation of the product sales site.
- An object of the present invention is to provide a product etc. information generating apparatus that automatically generates detailed information on products or services (hereinafter referred to as products etc.).
- the present invention relates to attribute storage means for storing attribute information for specifying the content of a product, etc. for each of a plurality of items related to the product, etc., reference attribute information as a reference for comparison of the product, etc., and a target product to be compared
- attribute information comparison means that compares attribute information such as for each item, attribute information such as target product for each item, and / or comparison information according to the comparison result, the contents of the target product etc.
- a product etc. information generating unit that generates product etc. information to be expressed, and the product etc. information generating unit relates to a product etc. information generating device that combines attribute information such as a target product for each item in a mode according to a comparison result.
- the product etc. information generating apparatus of the present invention it is possible to automatically generate detailed information on products or services (hereinafter referred to as products etc.).
- the recommended reason for the recommended product is not a “catch copy” that emphasizes only the merit of the product, but a product that is used by an excellent store clerk or salesman in the real world.
- Feature trade-off descriptions can be generated mechanically.
- the quality of the proposed method can be improved, and even in a situation where a vast number of products must be explained to an unspecified number of customers in non-face-to-face sales such as e-commerce, the trade of each product Not only can you explain the off, but also when used in actual face-to-face sales, it can be an assist when the start-up salesman etc.
- the attribute information comparison means determines the superiority or inferiority for each item by comparing the reference attribute information with the attribute information such as the target product, and the commodity information generation means is based on the determined superiority or inferiority Combination information specifying means for specifying combination information for combining attribute information and / or comparison information, and the product etc.
- information generating means specifies information corresponding to a plurality of attribute information and / or a plurality of comparison results. It is preferable to generate product etc. information by combining the combined information.
- the combination information is specified based on the superiority or inferiority of each item, and the product etc. information is generated using the specified combination information, thereby removing unnaturalness from the mechanically generated product etc. information. It is possible to provide a reason for recommendation with a higher degree of satisfaction.
- FIG. 1 It is a figure which shows the structure of a product etc. information generation system corresponding to at least 1 of embodiment of this invention. It is a block diagram which shows the structure of the terminal device corresponding to at least 1 of embodiment of this invention. It is a block diagram which shows the structure of the server apparatus corresponding to at least 1 of embodiment of this invention. It is a figure which shows an example of the display screen of a terminal device corresponding to at least 1 of embodiment of this invention. It is a figure showing the goods master table corresponding to at least one of the embodiments of the invention. It is a figure which shows an example of the flowchart of a goods etc. information generation process corresponding to at least 1 of embodiment of this invention.
- the present invention relates to a product etc. information generating apparatus, system, and program for generating a recommended (recommended) text relating to a product or service.
- a product etc. information generating system for generating a recommended text will be described.
- the services described below include not only services of private companies but also services provided by government agencies, and the present invention is not limited to this mode.
- FIG. 1 is a diagram showing a configuration of a product etc. information generation system corresponding to at least one of the embodiments of the present invention.
- the product etc. information generating system of the present invention is composed of a plurality of terminal devices 1 (terminal devices 1a, 1b... 1z), a communication network 2, and a server device 3.
- the terminal device 1 is connected to the server device 3 via the communication network 2.
- the terminal device 1 is a terminal through which a user browses products and makes purchases and applications. Examples of the terminal device include, but are not limited to, a personal computer, a smartphone, a tablet terminal, a mobile phone, and a PDA.
- the terminal device 1 may be any device that can be connected to the server device 3 via the communication network 2.
- As the communication network various known wired or wireless communication networks such as the Internet, a wired or wireless public telephone network, a wired or wireless LAN, and a dedicated line can be used.
- the server device 3 is a server device that transmits and receives information to and from the terminal device 1 and provides information to the terminal device 1.
- FIG. 2 is a block diagram showing a configuration of a terminal device corresponding to at least one of the embodiments of the present invention.
- the terminal device 1 includes a control unit 11, a RAM 12, a display unit 13, a display screen 13 a, a storage unit 14, an input unit 15, a communication interface 16, and the like, and the communication network 2 via the communication interface 16. Connected.
- the control unit 11 refers to and executes programs and data stored in a storage device such as the storage unit 14.
- the RAM 12 is a work area for the control unit 11.
- the display unit 13 has a display screen for displaying information on products and the like. Although not shown, a touch panel may be provided on the upper surface of the display unit 13. Input information can be received by pressing the touch panel with a stylus or a finger or moving the touch panel with a stylus or the like.
- the storage unit 14 is used as a storage area for storing programs and data, and can store data received from the server device 3.
- the input unit 15 includes a plurality of keys. Input information from the touch panel that can be provided in the input unit 15 and the display unit 13 is stored in the RAM 12.
- the control unit 11 executes various arithmetic processes based on the input information stored in the RAM 12.
- FIG. 3 is a block diagram showing a configuration of the server device corresponding to at least one of the embodiments of the present invention.
- the server device 3 includes a control unit 31, a RAM 32, a storage unit 33, and the like, and can be connected to the communication network 2 via the communication interface 34.
- the control unit 31 refers to and executes programs and data stored in the storage unit 33. Moreover, the control part 31 has a time measuring function.
- the RAM 32 is a work area for the control unit 31.
- the storage unit 33 stores data input in the terminal device 1, data received via the communication interface 34, and the like.
- the product etc. information generation system 4 has at least a reference attribute setting function, a comparison target product etc. extraction function, an attribute information comparison function, a comparison information extraction function, and a product etc. information generation function.
- the standard attribute setting function has a function to set a standard attribute that is a standard for comparing products.
- the comparison target product etc. extraction function has a function of extracting products etc. to be compared.
- the attribute information comparison function has a function of comparing, for each item, reference attribute information that is a reference for comparison of products and the like, and attribute information of target products that are comparison targets.
- the comparison information extraction function has a function of extracting a product or the like to be compared according to a predetermined condition.
- the product etc. information generation function has a function of generating product etc. information representing the content of the target product etc. by combining the attribute information of the target product etc. for each item and / or the comparison information according to the comparison result.
- a product browsing screen on a used car sales site is given as an example.
- the present invention is not limited to products like used cars, and may be applied to service applications.
- FIG. 4 is a diagram showing an example of a display screen of the terminal device corresponding to at least one of the embodiments of the present invention.
- a browsing screen 50 for products and the like is displayed on the display screen 13a of the terminal device 1.
- the product browsing screen 50 may be designed to be displayed by being selected by the user on the product list screen in which a plurality of selectable products are displayed on the display unit 13.
- the contents displayed on the product etc. list screen can be changed according to display conditions by setting display conditions by the user's operation.
- the product browsing screen 50 includes a product etc. name 51, product etc. image 52, product etc. attribute information 53, target product etc. 54, target product etc. attribute information 55, target product etc. information 56, and a favorite addition button 57. At least displayed.
- the product etc. name 51, the product etc. image 52, and the product etc. attribute information 53 are extracted from the product master table stored in the storage unit 33 of the server device 3 and displayed.
- FIG. 5 is a diagram showing a product master table corresponding to at least one of the embodiments of the present invention.
- the product master table 100 the manufacturer 102, the vehicle type 103, the year 104, the mileage 105, the next vehicle inspection 106, the repair history 107, the price 108, the smoking cessation 109, the displacement 110, the body type 111, the side are associated with the product No101.
- the airbag 112, the special note (excellent) 113, and the special note (inferior) 114 are stored at least. Other information may be appropriately increased according to the design.
- the product name 51 for example, information combining the manufacturer 102 and the vehicle type 103 is displayed.
- a product image stored in the storage unit 33 of the server device 3 is displayed based on link information (not shown) stored in the product master table.
- link information (not shown) stored in the product master table.
- attribute information 53 information on the year 104, mileage 105, next vehicle inspection 106, repair history 107, price 108, or a plurality of information is displayed in combination.
- other information stored in the product master table 100 such as the smoking cessation 109 and the displacement 110 may be displayed on the browsing screen 50.
- the target product etc. 54 displays a product etc. for comparison with the product displayed in FIG.
- the target product etc. attribute information 55 and the target product etc. information 56 information related to the target product etc. 54 is displayed. An information extraction method will be described later.
- the favorite addition button 57 is a button for causing the terminal device 1 or the server device 3 to store a product that the user likes in association with the user information.
- FIG. 6 is a diagram illustrating an example of a flowchart of product etc. information generation processing corresponding to at least one of the embodiments of the present invention. The following description will be made on products, but services are also included.
- the terminal device 1 accepts selection of a product from a plurality of products displayed on the display screen 13a by the user's operation (step S1), and displays the browsing screen 50.
- the product selected in step S1 is set as the reference product.
- Information related to the reference product (for example, information included in each item of the product master table 100) is also referred to as reference attribute information.
- the terminal device 1 transmits information that can identify the reference product selected in step S1 to the server device 3 (step S2).
- the server device 3 receives information that can identify the reference product (step S3).
- the server device 3 sets an extraction condition for extracting the target product to be compared based on the received reference attribute information regarding the reference product (step S4).
- the extraction condition is, for example, extracted under the condition that a value obtained by changing the price of the reference product 108 by 150,000 yen from the price of the reference product is an upper limit amount and a lower limit amount.
- the extraction condition set in step S4 is an initial condition and may be a fixed condition or a condition that varies according to the user's attribute.
- the server device 3 extracts a target product other than the reference product from the product master table 100 according to the extraction condition set in step S4 (step S5).
- the extraction conditions are changed as appropriate, and the extraction conditions are adjusted until the number of cases suitable for display is reached.
- the condition adjustment may be performed by incorporating a module provided by another service.
- the server device 3 compares the target product extracted in Step S5 with superiority or inferiority, and sets whether or not the attribute information of each item is superior to the reference product (Step S6).
- FIG. 7 is a diagram showing an superiority / inferiority master table corresponding to at least one of the embodiments of the present invention.
- the superior / inferior master table 130 stores superior conditions 133 and inferior conditions 134 in association with the item 131 and the reference attribute 132.
- Each column (item) stored in the item master table 100 corresponds to the item 131.
- the reference attribute 132 is determined according to the value of the attribute information of the reference product selected in step S1.
- the superiority condition 133 is a condition for determining that it is superior when compared with the reference attribute information.
- the inferior condition 134 is a condition for determining that the inferior condition is inferior when compared with the reference attribute information.
- the superior condition 133 is “the numerical value of the reference”. It is determined to be superior because it falls under “greater than”.
- the item 131 is “next vehicle inspection”
- the next vehicle inspection of the reference product is “December 2019”
- the next vehicle inspection of the comparison target product is “June 2018”
- the inferior condition 134 is Since it falls under “shorter than the standard”, it is determined to be inferior.
- the superiority or inferiority is determined for each attribute information of the comparison target product, and when it is determined that the product is superior (YES in step S7), the number of items determined to be superior is counted (step S8). On the other hand, if it is determined to be inferior (NO in step S7), nothing is done.
- FIG. 9 is a diagram showing a comparison result sentence master table corresponding to at least one of the embodiments of the present invention.
- a superior sentence 143, an inferior sentence 144, and a display order 145 are stored in association with the item 141 and the reference attribute 142.
- the superior sentence 143 is a sentence used when it is determined to be superior using the superior / inferior master table 130.
- the inferior sentence 144 is a sentence used when it is determined to be inferior using the superior / inferior master table 130.
- the display order 145 is information used when determining the order of items to be displayed in a text combination process described later.
- the server device 3 generates a sentence which is product etc. information for each target product.
- a target product is set (step S8), and sentence combination processing is performed for the set target product (step S9). Steps S8 and S9 are repeated until sentences are generated for all target products. The sentence combination process will be described later.
- the server device 3 transmits the target product information to the terminal device 1 (step S10).
- the terminal device 1 receives the target product information (step S11), displays the target product information on the display screen 13a (step S12), and ends the product etc. information generation process.
- FIG. 8 is a diagram showing an example of a flowchart of sentence combination processing corresponding to at least one of the embodiments of the present invention.
- the server device 3 extracts the item display order from the comparison result sentence master table (step S21).
- the server device 3 rearranges the attribute information of the target product in ascending or descending order of the display order 145 stored in the comparison result sentence master table 140 (step S22).
- the combination information is complemented between a plurality of items so that the attribute information corresponding to the items is established as a natural sentence.
- the complementing method an example of complementing conjunctions and particles as combination information will be described.
- step S23 items that have not yet been generated are set (step S23).
- step S24 it is determined whether the set item has a complementary item (step S24).
- the complementary item refers to an item having the same or similar information (also referred to as item property information) regarding the property of the product or the like indicated by the item.
- FIG. 10 is a diagram showing a complement master table corresponding to at least one of the embodiments of the invention.
- a relation type 152 is stored in association with the item 151.
- Items 151 having the same content of the relation type 152 are complementary items, and can be said to be in a complementary relationship.
- the complementary item is “travel distance” of the item having the same relation type 152. Since “year” represents the date of registration of the automobile, it can be used as an index representing the newness of the automobile. Similarly, the “travel distance” can also be used as an index indicating that the consumption of automobile parts is small, that is, it is close to a new product if the travel distance is short. Therefore, the items “year” and “travel distance” can be registered in the association type 152 as items representing “newness”.
- the association type 152 may be designed so that a plurality of types are stored as in the item 151 “body type”.
- the phrase (the previous phrase) of the item set in step S23 is set as the previous phrase (step S25). Further, as a subsequent phrase, a complementary item phrase (later phrase) is set (step S26).
- the “phrase” is, for example, a significant sentence. More specifically, the phrase may be only the comparison result sentence associated in step S7 or may be a sentence combined with attribute information. .
- step S27 it is determined whether the preceding phrase is dominant and the subsequent phrase is dominant. If it is determined to be true in step S27 (YES in step S27), the wording of the type of addition is set in the combination information (step S28).
- the wording of the type of addition includes, for example, “and”, “above”, “bonus”, “in addition”, and the like.
- step S29 If it is determined to be false in step S29 (NO in step S29), it is determined whether the previous phrase is inferior and the subsequent phrase is dominant (step S31). If it is determined to be true in step S31 (YES in step S31), the reverse type message is set in the combination information (step S32).
- the wording of the reverse connection type includes, for example, “but”, “however”, “where”, “what”.
- step S31 If it is determined to be false in step S31 (NO in step S31), the processing target item is set to processed.
- the combination information is complemented between the previous phrase and the subsequent phrase to generate an intermediate sentence (step S33), and the processing target item and the supplemental item are set as processed.
- the intermediate text is a logical recommended text that combines merits and demerits regarding items such as products, and is part or all of the product information.
- the “year” of the standard attribute car is “2007”, the “travel distance” is “51,000 km”, and the “year” of the target product is “2016”, “travel”
- the preceding phrase is “new year” and the following phrase is “traveling distance is short”, which is set in step S28.
- the combination information is the wording of the type of addition. Therefore, the intermediate sentences created in step S33 are ““ Year is new ”,“ Furthermore ”,“ Small mileage ”.
- the “year” of the standard attribute car is “2007”
- the “travel distance” is “51,000 km”
- the “year” of the target product is “2012”
- the “travel distance” is “8.
- the preceding phrase is dominant and the latter phrase is inferior.
- the previous phrase is “new year”
- the later phrase is “having a lot of mileage”
- the combination information set in step S28 is a supplementary wording. Therefore, the intermediate sentence created in step S33 is ““ Year is new ”,“ However, ”“ Movement distance is large ”.
- the method of generating a sentence using the superiority / inferiority master table 130 and the comparison result sentence master table 140 has the following effects as compared to a method of constructing sentences by applying words to a template. .
- the fitting process to the template is multi-layered and increases the calculation processing load.
- the method of the present invention only determines the causal relationship between attributes and the combination processing using conjunctions, and keeps the calculation processing load low. be able to. As a result, the display speed is also improved, and user discomfort can be reduced.
- the reference product is the product selected by the user.
- the user's preference and interest / interest data input in advance may be determined as the reference product.
- the user may be able to input and specify information related to the reference product.
- the user can receive proposals based on the user's interests and interests without searching for the product etc., by inputting the reference attributes as appropriate according to the user's own preferences. Can be
- a value derived from the history data of the product viewed by the user for example, an average value, the number of times of browsing, the time of browsing, or the like may be used as the reference attribute.
- the user can generate a standard without being conscious of it, and make the user aware of the potential needs that the user does not recognize and appeal to them accordingly. can do.
- the user's reference attribute may be generated based on information on products and the like added by the user operating the favorite addition button 57. In this way, it is possible to save time and effort for the user to directly input the reference information, and it is possible to efficiently generate the reference information that accurately reflects the user's preference.
- the user's reference attribute is not shown, for example, an axis may be provided for each item representing the reference attribute and displayed as a polygonal radar chart. Further, the radar chart value may be designed to be changeable by the user. By doing in this way, it becomes easy for a user to grasp
- the user's reference attribute is displayed as a rater chart, the user may check the chart and edit the attribute that he / she wants to prioritize or does not want to prioritize. In this way, by visualizing the user's potential and unconditionally defined conditions, it is possible to clearly show the user the standard attributes that are the basis for the system proposal, giving the user a sense of security and satisfaction. be able to.
- intermediate sentences are generated by combining complementary items in the complementary master table.
- the intermediate sentence may be generated using items that match the user's preference. That is, even if the item is not in a complementary relationship, an intermediate sentence may be generated by combining information on the superior item. For example, when a black-colored car meets the user's preference, an intermediate sentence such as “the body type is hatchback and the body color is black” can be generated. By doing so, it is possible to automatically generate a persuasive sentence with a wide range of combinations of items and showing the basis.
- a proposal reflecting the user's hobbies and preferences can be received, and the advertising effect that stimulates the user's willingness to purchase can be expected more.
- the display order 145 stored in the comparison result text master table 140 is not updated, but the user may be able to update the display order 145.
- the operation history information of the user may be used as input information and automatically updated using a machine learning algorithm. Specifically, based on operation history information of a plurality of users who use the system, the users are classified and updated to the display rank 145 corresponding to the classification. For example, when the color of the product viewed by the user A is only “red”, the display order suitable for the classification of the user who is viewing the red product can be determined by the machine learning algorithm.
- the above example is simple, it is possible to automatically set a display order with higher accuracy by limiting input information within a predetermined period or using a plurality of input information. By doing in this way, goods etc. information can be generated with the display order which grasped a user's tendency appropriately, and a sentence can be automatically generated from an item predicted to be higher interest for the user.
- Machine learning is an autonomous process in which a computer device repeatedly learns data, recognizes patterns and empirical rules in the data, and then applies the patterns and empirical rules to unknown data. A method for deriving answers. In particular, it can be applied to regression problems and classification problems.
- Machine learning includes, for example, supervised learning that generates a function that maps the input and the output that should correspond to it, unsupervised learning that builds a model from only the input, and behavior to be observed by observing the surrounding environment There is reinforcement learning to do.
- Supervised learning is, for example, discriminant analysis, support vector machine, Bayesian network, or the like.
- Unsupervised learning includes data clustering and principal component analysis. Reinforcement learning is, for example, Q learning or a Markov decision process.
- deep learning in which feature amounts representing features of input learning data are automatically acquired and learned.
- FIG. 11 is a diagram illustrating a hierarchical neural network corresponding to at least one of the embodiments of the present invention.
- a description will be given of an output (result) z for an input x (x 1 , x 2 ,..., X n ).
- a weight w (w 1 , w 2 ,..., W n ) corresponding to each input x is set, and z is output by multiplying x and w corresponding to x.
- the neural network shown in FIG. 11 is called a simple perceptron model.
- FIG. 12 is a diagram illustrating a multilayer neural network corresponding to at least one of the embodiments of the invention.
- the multilayer neural network has an intermediate layer in addition to the neural network of FIG.
- the intermediate layer may have a plurality of layers. Similar to FIG. 11, weights are set on edges connecting nodes.
- the input value passed to each node in the intermediate layer is the sum of values obtained by multiplying the value of each node in the input layer by the weight set for the edge.
- the input value passed to each node in the output layer is the sum of the values multiplied by the weight.
- the result output by the machine learning algorithm may be output every time a user operation is accepted, or may be output every elapse of a predetermined period.
- the machine learning algorithm is preferably generated by setting given parameters so that, for example, the weight related to the purchase of a product is the largest, the inquiry is the second largest, and the browsing is the smallest.
- a natural language analysis technique may be realized by using a machine learning algorithm. For example, a user's comment posted on the product page may be analyzed to generate a text representing the characteristics of the product that is not stored in the comparison result text master table 140. By doing in this way, the characteristic of the goods based on the impression which the user actually used can be expressed, and the appeal power to the user who chooses goods can be raised more.
- a technique of a neural network including a convolution layer and a pooling layer may be used.
- characteristic information of a product can be extracted from an image representing the product using CNN.
- features can be mechanically extracted from product photo data, and product features can be dynamically changed.
- product refers to, for example, an item that is a target of commercial transaction, and may be tangible or intangible, and is a concept that includes not only movable property but also real estate.
- Service refers to, for example, labor or benefit for another person, which is subject to commercial transactions independently. In the embodiment of the present invention, transactions include free transactions that do not involve payment of consideration.
- “combination information” is, for example, information used for a combination and includes a conjunction.
- “Item property information” is, for example, information indicating the property of an item, and is information indicating the feature, element, purpose, etc. of the item.
- the “computer device” refers to, for example, a desktop or notebook personal computer, a tablet computer, or a PDA, and may be a portable terminal including a touch panel sensor on a display screen.
- Attribute storage means for storing attribute information for specifying the content of a product or the like for each of a plurality of items related to the product or service (hereinafter referred to as a product or the like); Attribute information comparison means for comparing, for each item, standard attribute information that is a reference for comparison of products and the like, and attribute information of target products and the like to be compared, Commodity information generating means for generating product etc. information representing the content of the target product etc. by combining the attribute information of the target product etc. for each item and / or the comparison information according to the comparison result, A product etc. information generating device, wherein the product etc. information generating means combines attribute information such as a target product for each item in a mode according to the comparison result.
- the attribute information comparison means determines the superiority or inferiority of each item by comparing the reference attribute information with the attribute information such as the target product
- Commodity information generating means comprises combination information specifying means for specifying combination information for combining attribute information and / or comparison information based on the determined superiority or inferiority
- the product etc. information generating device further includes With regard to the combination of attribute information in the product information generation means, the combination storage means for storing other items corresponding to the attribute information preferentially combined with the attribute information of one item, The product etc. information generating means combines the attribute information of one item such as the target product with the attribute information of another item preferentially combined with the attribute information of the one item. Generate product etc. information that represents the content, The product etc. information generating device described in [1] or [2].
- the product etc. information generating device further includes Priority storage means for storing the priority for each item of attribute information used for generating product etc. information in the product etc. information generating means;
- the product etc. information generating means generates product etc. information by combining the attribute information of the target product etc. for each item based on the priority stored in the priority storage means.
- [1] to [3] The product etc. information generating apparatus according to any one of the above.
- the product etc. information generating device further includes: A reference attribute input means for receiving input of reference attribute information by a user operation is provided.
- the product information generation device according to any one of [1] to [4], wherein the attribute information comparison unit compares the received reference attribute information with the attribute information of the target product for each item.
- the display means displays information about the product etc. by the user's operation
- the product etc. information generating device further An interest product etc. storage means for storing information on products etc. displayed by the display means by the user's operation as an interest product etc.,
- the product etc. information generating apparatus according to [6] or [7], wherein the reference attribute setting unit sets the reference attribute information based on the attribute information for each item such as the product stored in the product etc. storage unit of interest.
- a product etc. information generation program for generating product etc. information representing the content of a product or service (hereinafter referred to as product etc.) executed in a computer device, Attribute storage means for storing attribute information for specifying the content of a product, etc. for each of a plurality of items related to the product, etc.
- Attribute information comparison means for comparing, for each item, reference attribute information that is a reference for comparison of products and the like, and attribute information of target products that are comparison targets, By combining attribute information such as the target product for each item and / or comparison information according to the comparison result, it functions as a product etc. information generating means for generating product etc. information representing the content of the target product etc.
- the product etc. information generating program combines the attribute information of the target product etc. for each item in a mode according to the comparison result.
- a system comprising a computer device and a server device connectable to the computer device by communication, Attribute storage means for storing attribute information for specifying the content of a product or the like for each of a plurality of items relating to a product or service (hereinafter referred to as a product or the like); Attribute information comparison means for comparing, for each item, standard attribute information that is a reference for comparison of products and the like, and attribute information of target products and the like to be compared, Commodity information generating means for generating product etc. information representing the content of the target product etc. by combining the attribute information of the target product etc. for each item and / or the comparison information according to the comparison result, A product etc. information generating system, wherein the product etc. information generating means combines attribute information such as target products for each item in a mode according to the comparison result.
- a product etc. information generation method for generating product etc. information representing the content of a product or service executed in a computer device, A step of comparing, for each item, reference attribute information that is a reference for comparison of products and the like, and attribute information of target products and the like that are targets of comparison; Generating attribute information such as target product for each item and / or comparison information according to the comparison result, and generating product etc. information representing the content of the target product by the control unit,
- the step of generating the product etc. information is a product etc. information generation method in which the attribute information such as the target product for each item is combined in a mode according to the comparison result.
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Abstract
Description
図8は、本発明の実施の形態の少なくとも1つに対応する、文章組合せ処理のフローチャートの一例を示す図である。サーバ装置3は、項目表示順位を比較結果文章マスタテーブルから抽出する(ステップS21)。サーバ装置3は、対象商品の属性情報を比較結果文章マスタテーブル140に記憶された表示順位145の昇順又は降順に並べ替える(ステップS22)。
上で述べた実施の形態の説明は、下記の発明を、発明の属する分野における通常の知識を有する者がその実施をすることができるように記載した。
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段と、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段と
を備え、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成装置。
商品等情報生成手段が、決定された優劣に基づいて、属性情報及び/又は比較情報を組み合わせるための組合せ情報を特定する組合せ情報特定手段とを備え、
商品等情報生成手段が、複数の属性情報及び/又は複数の比較結果に応じた情報と特定された組合せ情報とを組み合わせることで商品等情報を生成する、[1]に記載の商品等情報生成装置。
商品等情報生成手段における属性情報の組み合わせに関して、一の項目の属性情報に対して優先的に組み合わされる属性情報に対応する他の項目を記憶する組合記憶手段を備え、
商品等情報生成手段が、対象商品等の一の項目についての属性情報を、該一の項目の属性情報に対して優先的に組み合わされる他の項目の属性情報と組み合わせることで、対象商品等の内容を表す商品等情報を生成する、
[1]又は[2]に記載された商品等情報生成装置。
商品等情報生成手段における商品等情報の生成に利用される属性情報の項目ごとの優先度を記憶する優先度記憶手段と、
商品等情報生成手段が、優先度記憶手段に記憶された優先度をもとに、項目ごとの対象商品等の属性情報を組み合わせることで商品等情報を生成する、[1]~[3]のいずれかに記載の商品等情報生成装置。
ユーザの操作により、基準属性情報の入力を受け付ける基準属性入力手段
を備え、
属性情報比較手段が、受け付けた基準属性情報と、対象商品等の属性情報とを項目ごとに比較する、[1]~[4]のいずれかに記載の商品等情報生成装置。
商品等に関する情報を表示する表示手段と、
表示された商品等に関する情報を基準属性情報として設定する基準属性設定手段と
を備え、
属性情報比較手段が、設定された基準属性情報と、対象商品等の属性情報とを項目ごとに比較する、[1]~[4]のいずれかに記載の商品等情報生成装置。
商品等情報生成装置がさらに、
基準属性設定手段が、表示手段により表示された商品等の項目ごとの属性情報の履歴に基づいて、基準属性情報を設定する、[6]に記載の商品等情報生成装置。
商品等情報生成装置がさらに、
ユーザの操作により表示手段により表示された商品等に関する情報を関心商品等として記憶する関心商品等記憶手段と
を備え、
基準属性設定手段が、関心商品等記憶手段に記憶された商品等の項目ごとの属性情報に基づいて、基準属性情報を設定する、[6]又は[7]に記載の商品等情報生成装置。
コンピュータ装置を
商品等に関する複数の項目ごとに、商品等の内容を特定する属性情報を記憶する属性記憶手段、
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段
として機能させ、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成プログラム。
商品又はサービス(以下、商品等という)に関する複数の項目ごとに、商品等の内容を特定する属性情報を記憶する属性記憶手段と、
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段と、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段と
を備え、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成システム。
制御部により、商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較するステップと、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、制御部により、対象商品等の内容を表す商品等情報を生成するステップと
を有し、
商品等情報を生成するステップは、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成方法。
2 通信ネットワーク
3 サーバ装置
4 商品等情報生成システム
11 制御部
12 RAM
13 表示部
14 ストレージ部
15 入力部
16 通信インタフェース
31 制御部
32 RAM
33 ストレージ部
34 通信インタフェース
100 商品マスタテーブル
130 優劣マスタテーブル
140 比較結果文章マスタテーブル
150 補完マスタテーブル
Claims (7)
- 商品又はサービス(以下、商品等という)に関する複数の項目ごとに、商品等の内容を特定する属性情報を記憶する属性記憶手段と、
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段と、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段と
を備え、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成装置。 - 属性情報比較手段が、基準属性情報と対象商品等の属性情報との比較により、項目ごとの優劣を決定するものであって、
商品等情報生成手段が、決定された優劣に基づいて、属性情報及び/又は比較情報を組み合わせるための組合せ情報を特定する組合せ情報特定手段とを備え、
商品等情報生成手段が、複数の属性情報及び/又は複数の比較結果に応じた情報と特定された組合せ情報とを組み合わせることで商品等情報を生成する、請求項1に記載の商品等情報生成装置。 - 商品等情報生成装置がさらに、
商品等情報生成手段における属性情報の組み合わせに関して、一の項目の属性情報に対して優先的に組み合わされる属性情報に対応する他の項目を記憶する組合記憶手段を備え、
商品等情報生成手段が、対象商品等の一の項目についての属性情報を、該一の項目の属性情報に対して優先的に組み合わされる他の項目の属性情報と組み合わせることで、対象商品等の内容を表す商品等情報を生成する、
請求項1又は2に記載された商品等情報生成装置。 - 商品等情報生成装置がさらに、
商品等情報生成手段における商品等情報の生成に利用される属性情報の項目ごとの優先度を記憶する優先度記憶手段と、
商品等情報生成手段が、優先度記憶手段に記憶された優先度をもとに、項目ごとの対象商品等の属性情報を組み合わせることで商品等情報を生成する、請求項1~3のいずれかに記載の商品等情報生成装置。 - コンピュータ装置において実行される、商品又はサービス(以下、商品等という)の内容を表す商品等情報を生成する商品等情報生成プログラムであって、
コンピュータ装置を
商品等に関する複数の項目ごとに、商品等の内容を特定する属性情報を記憶する属性記憶手段、
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段
として機能させ、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成プログラム。 - コンピュータ装置と、該コンピュータ装置と通信により接続可能なサーバ装置を備える商品等情報生成システムであって、
商品又はサービス(以下、商品等という)に関する複数の項目ごとに、商品等の内容を特定する属性情報を記憶する属性記憶手段と、
商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較する属性情報比較手段と、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、対象商品等の内容を表す商品等情報を生成する商品等情報生成手段と
を備え、
商品等情報生成手段は、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成システム。 - コンピュータ装置において実行される商品又はサービス(以下、商品等という)の内容を表す商品等情報を生成する商品等情報生成方法であって、
制御部により、商品等の比較の基準となる基準属性情報と、比較の対象となる対象商品等の属性情報とを、項目ごとに比較するステップと、
項目ごとの対象商品等の属性情報、及び/又は、比較結果に応じた比較情報を組み合わせることで、制御部により、対象商品等の内容を表す商品等情報を生成するステップと
を有し、
商品等情報を生成するステップは、比較結果に応じた態様で、項目ごとの対象商品等の属性情報を組み合わせる、商品等情報生成方法。
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JP2003022395A (ja) * | 2001-07-05 | 2003-01-24 | Matsushita Electric Ind Co Ltd | 商品関連情報提供システム、商品販売システム |
JP2004362289A (ja) * | 2003-06-05 | 2004-12-24 | Oki Electric Ind Co Ltd | 商品情報提供支援システム |
US20080215349A1 (en) * | 2003-05-07 | 2008-09-04 | Cnet Networks | System and method for generating an alternative product recommendation |
JP2010237790A (ja) * | 2009-03-30 | 2010-10-21 | Sharp Corp | 製品情報比較表示装置及び製品情報比較表示方法 |
WO2016075835A1 (ja) * | 2014-11-14 | 2016-05-19 | 富士通株式会社 | 旅程決定方法、旅程決定プログラムおよび旅程決定装置 |
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JP2003022395A (ja) * | 2001-07-05 | 2003-01-24 | Matsushita Electric Ind Co Ltd | 商品関連情報提供システム、商品販売システム |
US20080215349A1 (en) * | 2003-05-07 | 2008-09-04 | Cnet Networks | System and method for generating an alternative product recommendation |
JP2004362289A (ja) * | 2003-06-05 | 2004-12-24 | Oki Electric Ind Co Ltd | 商品情報提供支援システム |
JP2010237790A (ja) * | 2009-03-30 | 2010-10-21 | Sharp Corp | 製品情報比較表示装置及び製品情報比較表示方法 |
WO2016075835A1 (ja) * | 2014-11-14 | 2016-05-19 | 富士通株式会社 | 旅程決定方法、旅程決定プログラムおよび旅程決定装置 |
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