Interior-layout assistance method, interior-layout assistance system, and program

An interior-layout assistance method, comprising:

• a first step of acquiring or generating three-dimensional (3D) computer-aided-design (CAD) data of an interior;
• a second step of receiving designation of a classification of, and a budget for, a product, the product being at least one of a furniture and a home appliance, to be arranged in the interior, the designation being received from a user;
• a third step of determining a plurality of arrangement candidates that are presented as different combinations of a space in which the product can be arranged among spaces in the interior and the product to be arranged in the space, the determining of the plurality of arrangement candidates being performed on a basis of the 3D CAD data acquired or generated in the first step and of the classification of and the budget for the product, the classification and the budget being designated in the second step;
• a fourth step of displaying a 3D CAD image in which the product is arranged in the space in which the product can be arranged, the displaying of the 3D CAD image being performed with regard to each of the plurality of arrangement candidates determined in the third step;
• a fifth step of
• displaying a selection screen that allows selection of another product in a same classification as a classification of the product being displayed, the displaying of the selection screen being performed in response to designation of the product by the user via the 3D CAD image displayed in the fourth step, and
• generating 3D CAD data of an arrangement of the other product in response to the selection of the other product via the selection screen;
• and
• a sixth step of:
• associating 3D CAD data of interiors of users who have ever purchased products, a plurality of arrangement candidates selected by the users, and a product purchased by the user with each other as history data, and
• storing the history data into a memory,
• the first step, the second step, the third step, the fourth step, the fifth step, and the sixth step being carried out by a computer,
• the third step including determining, as arrangement candidates and products with high priorities, arrangement candidates and products that correspond to combinations with high similarity to a combination of the 3D CAD data of the interior, the designated classification, and the budget corresponding to the designated classification among the arrangement candidates and the products that have ever been selected by the other users, the determining of the arrangement candidates and the products with the high priorities being performed on a basis of the history data stored in the memory in the sixth step,
• the third step including determining the plurality of arrangement candidates and the products with use of a learning model obtained by machine learning in which combinations of the 3D CAD data of the interiors of the users who have ever purchased the products, the plurality of arrangement candidates selected by the users, the product purchased by the user, and attributes of the users are used as training data.

A program, stored on a non-transitory computer-readable storage medium, for causing a computer to carry out:

• a first step of acquiring or generating three-dimensional (3D) computer-aided-design (CAD) data of an interior;
• a second step of receiving designation of a classification of, and a budget for, a product, the product being at least one of a furniture and a home appliance, to be arranged in the interior, the designation being received from a user;
• a third step of determining a plurality of arrangement candidates that are presented as different combinations of a space in which the product can be arranged among spaces in the interior and the product to be arranged in the space, the determining of the plurality of arrangement candidates being performed on a basis of the 3D CAD data acquired or generated in the first step and of the classification of and the budget for the product, the classification and the budget being designated in the second step;
• a fourth step of displaying a 3D CAD image in which the product is arranged in the space in which the product can be arranged, the displaying of the 3D CAD image being performed with regard to each of the plurality of arrangement candidates determined in the third step;
• a fifth step of:
• displaying a selection screen that allows selection of another product in a same classification as a classification of the product being displayed, the displaying of the selection screen being performed in response to designation of the product by the user via the 3D CAD image displayed in the fourth step, and
• generating 3D CAD data of an arrangement of the other product in response to the selection of the other product via the selection screen;
• and
• a sixth step of:
• associating 3D CAD data of interiors of users who have ever purchased products, the products purchased by the users, and prices of the products purchased by the users with each other as history data, and
• storing the history data into a memory,
• the third step including executing a process of
• determining the plurality of arrangement candidates and products with use of a learning model obtained by machine learning in which combinations of the 3D CAD data of the interiors of the users who have ever purchased the products and the products purchased by the users are used as training data, and
• displaying, as arrangement candidates and products with high priorities, arrangement candidates and products that correspond to combinations with high similarity to a combination of the 3D CAD data of the interior, the designated classification, and the budget corresponding to the designated classification, the displaying of the arrangement candidates and the products with the high priorities being performed on a basis of the history data stored in the memory in the sixth step and from among the plurality of determined arrangement candidates and the determined products among the arrangement candidates and the products that have ever been selected by the other users.

A program, stored on a non-transitory computer-readable storage medium, for causing a computer to carry out:

• a first step of acquiring or generating three-dimensional (3D) computer-aided-design (CAD) data of an interior;
• a second step of receiving designation of a classification of, and a budget for, a product, the product being at least one of a furniture and a home appliance, to be arranged in the interior, the designation being received from a user;
• a third step of determining a plurality of arrangement candidates that are presented as different combinations of a space in which the product can be arranged among spaces in the interior and the product to be arranged in the space, the determining of the plurality of arrangement candidates being performed on a basis of the 3D CAD data acquired or generated in the first step and of the classification of and the budget for the product, the classification and the budget being designated in the second step;
• a fourth step of displaying a 3D CAD image in which the product is arranged in the space in which the product can be arranged, the displaying of the 3D CAD image being performed with regard to each of the plurality of arrangement candidates determined in the third step;
• a fifth step of:
• displaying a selection screen that allows selection of another product in a same classification as a classification of the product being displayed, the displaying of the selection screen being performed in response to designation of the product by the user via the 3D CAD image displayed in the fourth step, and
• generating 3D CAD data of an arrangement of the other product in response to the selection of the other product via the selection screen;
• and
• a sixth step of:
• associating 3D CAD data of interiors of users who have ever purchased products, a plurality of arrangement candidates selected by the users, and a product purchased by the user with each other as history data, and
• storing the history data into a memory,
• the third step including determining, as arrangement candidates and products with high priorities, arrangement candidates and products that correspond to combinations with high similarity to a combination of the 3D CAD data of the interior, the designated classification, and the budget corresponding to the designated classification among the arrangement candidates and the products that have ever been selected by the other users, the determining of the arrangement candidates and the products with the high priorities being performed on a basis of the history data stored in the memory in the sixth step,
• the third step including determining the plurality of arrangement candidates and the products with use of a learning model obtained by machine learning in which combinations of the 3D CAD data of the interiors of the users who have ever purchased the products, the plurality of arrangement candidates selected by the users, the product purchased by the user, and attributes of the users are used as training data.

An interior-layout assistance system, comprising:

• first means for acquiring or generating three-dimensional (3D) computer-aided-design (CAD) data of an interior;
• second means for receiving designation of a classification of, and a budget for, a product, the product being at least one of a furniture and a home appliance, to be arranged in the interior, the designation being received from a user;
• third means for determining a plurality of arrangement candidates that are presented as different combinations of a space in which the product can be arranged among spaces in the interior and the product to be arranged in the space, the determining of the plurality of arrangement candidates being performed on a basis of the 3D CAD data acquired or generated by the first means and of the classification of and the budget for the product, the classification and the budget being designated by the second means;
• fourth means for displaying a 3D CAD image in which the product is arranged in the space in which the product can be arranged, the displaying of the 3D CAD image being performed with regard to each of the plurality of arrangement candidates determined by the third means;
• fifth means for:
• displaying a selection screen that allows selection of another product in a same classification as a classification of the product being displayed, the displaying of the selection screen being performed in response to designation of the product by the user via the 3D CAD image displayed by the fourth means, and
• generating 3D CAD data of an arrangement of the other product in response to the selection of the other product via the selection screen;
• and
• sixth means for:
• associating 3D CAD data of interiors of users who have ever purchased products, the products purchased by the users, and prices of the products purchased by the users with each other as history data, and
• storing the history data into a memory,
• the third means executing a process of
• determining the plurality of arrangement candidates and products with use of a learning model obtained by machine learning in which combinations of the 3D CAD data of the interiors of the users who have ever purchased the products and the products purchased by the users are used as training data, and
• displaying, as arrangement candidates and products with high priorities, arrangement candidates and products that correspond to combinations with high similarity to a combination of the 3D CAD data of the interior, the designated classification, and the budget corresponding to the designated classification, the displaying of the arrangement candidates and the products with the high priorities being performed on a basis of the history data stored in the memory by the sixth means and from among the plurality of determined arrangement candidates and the determined products among the arrangement candidates and the products that have ever been selected by the other users.

An interior-layout assistance system, comprising:

• first means for acquiring or generating three-dimensional (3D) computer-aided-design (CAD) data of an interior;
• second means for receiving designation of a classification of, and a budget for, a product, the product being at least one of a furniture and a home appliance, to be arranged in the interior, the designation being received from a user;
• third means for determining a plurality of arrangement candidates that are presented as different combinations of a space in which the product can be arranged among spaces in the interior and the product to be arranged in the space, the determining of the plurality of arrangement candidates being performed on a basis of the 3D CAD data acquired or generated by the first means and of the classification of and the budget for the product, the classification and the budget being designated by the second means;
• fourth means for displaying a 3D CAD image in which the product is arranged in the space in which the product can be arranged, the displaying of the 3D CAD image being performed with regard to each of the plurality of arrangement candidates determined by the third means;
• fifth means for:
• displaying a selection screen that allows selection of another product in a same classification as a classification of the product being displayed, the displaying of the selection screen being performed in response to designation of the product by the user via the 3D CAD image displayed by the fourth means, and
• generating 3D CAD data of an arrangement of the other product in response to the selection of the other product via the selection screen;
• and
• sixth means for:
• associating 3D CAD data of interiors of users who have ever purchased products, a plurality of arrangement candidates selected by the users, and a product purchased by the user with each other as history data, and
• storing the history data into a memory,
• the third means determining, as arrangement candidates and products with high priorities, arrangement candidates and products that correspond to combinations with high similarity to a combination of the 3D CAD data of the interior, the designated classification, and the budget corresponding to the designated classification among the arrangement candidates and the products that have ever been selected by the other users, the determining of the arrangement candidates and the products with the high priorities being performed on a basis of the history data stored in the memory by the sixth means,
• the third means determining the plurality of arrangement candidates and the products with use of a learning model obtained by machine learning in which combinations of the 3D CAD data of the interiors of the users who have ever purchased the products, the plurality of arrangement candidates selected by the users, the product purchased by the user, and attributes of the users are used as training data.