Server, analysis method and computer program product

Abstract

According to an embodiment, a server includes a first acquiring unit, a second acquiring unit, an analyzing unit, and an output unit. The first acquiring unit is configured to acquire recognition information includes a product identification information for identifying the product. The second acquiring unit is configured to acquire combination information including the product identification information of the product to be combined with an object image including an object. The analyzing unit is configured to calculate product priorities for respective products by analyzing the recognition information and the combination information. The output unit is configured to output information based on the product priorities.

What is claimed is: 
     
         1 . A server comprising:
 a first acquiring unit configured to acquire a piece of recognition information including a piece of product identification information for identifying a product included in a product image;   a recognition information storage unit configured to store the piece of recognition information;   a second acquiring unit configured to acquire a piece of combination information including the piece of product identification information of the product to be combined with an object image including an object;   a combination information storage unit configured to store the piece of combination information;   an analyzing unit configured to calculate product priorities for respective products by analyzing a plurality of pieces of recognition information stored in the recognition information storage unit and a plurality of pieces of combination information stored in the combination information storage unit; and   an output unit configured to output information based on the product priorities.   
     
     
         2 . The server according to  claim 1 , wherein
 the analyzing unit calculates the product priorities on the basis of first product priorities for the respective products and second product priorities for the respective products,   the analyzing unit calculates the first product priorities by analyzing the pieces of recognition information, and   the analyzing unit calculates the second product priorities by analyzing the pieces of combination information.   
     
     
         3 . The server according to  claim 2 , wherein
 each piece of recognition information includes date and time of recognition,   each piece of combination information includes date and time of combination,   the analyzing unit sets, to a higher level, the first product priority of the product represented by the piece of product identification information associated with the date and time of recognition closer to current date and time by analyzing the pieces of recognition information, and   the analyzing unit sets, to a higher level, the second product priority of the product represented by the piece of product identification information associated with the date and time of combination closer to the current date and time by analyzing the pieces of combination information.   
     
     
         4 . The server according to  claim 2 , wherein
 the analyzing unit sets, to a higher level, the first product priority of the product represented by the piece of product identification information having a value whose number of occurrences is larger by analyzing the pieces of recognition information, and   the analyzing unit sets, to a higher level, the second product priority of the product represented by the piece of product identification information having a value whose number of occurrences is larger by analyzing the pieces of combination information.   
     
     
         5 . The server according to  claim 1 , wherein
 each piece of recognition information includes a plurality of kinds of related information relating to the product,   the analyzing unit further analyzes whether there is a piece of combination information including the piece of product identification information of the product whose product priority satisfies a first predetermined condition in the pieces of combination information, and generates first recommendation information for recommending related information on the basis of a result of the analysis among the kinds of related information, and   the output unit outputs information based on the product priority and the first recommendation information to the recognizing unit.   
     
     
         6 . The server according to  claim 1 , wherein
 each piece of combination information includes an image for combination,   the image for combination is provided for each category of product,   each of the pieces of combination information includes a category of the corresponding product,   if there is a plurality of categories of a product whose product priority satisfies a second predetermined condition, the analyzing unit analyzes the number of occurrences of each of the categories in the pieces of combination information and generates second recommendation information for recommending the category with the largest number of occurrences, and   the output unit outputs information based on the product priority and the second recommendation information to the combining unit.   
     
     
         7 . A server comprising:
 a first acquiring unit configured to acquire a piece of recognition information including a piece of product identification information for identifying a product included in a product image;   a recognition information storage unit configured to store the piece of recognition information;   a second acquiring unit configured to acquire a piece of combination information including the piece of product identification information of the product to be combined with an object image including an object;   a combination information storage unit configured to store the piece of combination information;   a third acquiring unit configured to acquire a piece of sales promotion information relating to sales promotion of the product and a piece of purchase information including at least the piece of product identification information of the product;   a sales information storage unit configured to store the piece of sales promotion information and the piece of purchase information;   an analyzing unit configured to perform at least one of first analysis and second analysis, the first analysis calculating product priorities for respective products by analyzing a plurality of pieces of recognition information stored in the recognition information storage unit, a plurality of pieces of combination information stored in the combination information storage unit, and a plurality of pieces of purchase information stored in the sales information storage unit, the second analysis obtaining updated contents of the pieces of sales promotion information by analyzing at least either the pieces of recognition information or the pieces of combination information in addition to the pieces of purchase information; and   an output unit configured to output at least one of information based on the product priorities and the updated contents.   
     
     
         8 . The server according to  claim 7 , wherein
 the analyzing unit calculates the product priorities on the basis of first product priorities for the respective products, second product priorities for the respective products, and third product priorities for the respective products,   the analyzing unit calculates the first product priorities by analyzing the pieces of recognition information,   the analyzing unit calculates the second product priorities by analyzing the pieces of combination information, and   the analyzing unit calculates the third product priorities by analyzing the pieces of purchase information.   
     
     
         9 . The server according to  claim 8 , wherein
 the analyzing unit sets, to a higher level, the first product priority of the product represented by the piece of product identification information having a value whose number of occurrences is larger by analyzing the pieces of recognition information,   the analyzing unit sets, to a higher level, the second product priority of the product represented by the piece of product identification information having a value whose number of occurrences is larger by analyzing the pieces of combination information, and   the analyzing unit sets, to a higher level, the third product priority of the product represented by the piece of product identification information having a value whose number of occurrences is larger by analyzing the pieces of purchase information.   
     
     
         10 . The server according to  claim 8 , wherein
 each piece of recognition information includes date and time of recognition,   each piece of combination information includes date and time of combination,   each piece of purchase information includes date and time of purchase,   the analyzing unit sets, to a higher level, the first product priority of the product represented by the piece of product identification information associated with the date and time of recognition closer to current date and time by analyzing the pieces of recognition information,   the analyzing unit sets, to a higher level, the second product priority of the product represented by the piece of product identification information associated with the date and time of combination closer to the current date and time by analyzing the pieces of combination information, and   the analyzing unit sets, to a higher level, the third product priority of the product represented by the piece of product identification information associated with the date and time of purchase closer to the current date and time by analyzing the pieces of purchase information.   
     
     
         11 . The server according to  claim 7 , wherein
 each piece of recognition information includes a plurality of kinds of related information relating to the product,   the analyzing unit further analyzes whether there is a piece of combination information including the piece of product identification information of the product whose product priority satisfies a first predetermined condition in the pieces of combination information, and generates first recommendation information for recommending related information on the basis of a result of the analysis among the kinds of related information, and   the output unit outputs information based on the product priority and the first recommendation information to the recognizing unit.   
     
     
         12 . The server according to  claim 7 , wherein
 each piece of combination information includes an image for combination,   each of the pieces of combination information includes a category of the corresponding product,   if there is a plurality of categories of a product whose product priority satisfies a second predetermined condition, the analyzing unit analyzes the number of occurrences of each of the categories in the pieces of combination information and generates second recommendation information for recommending the category with the largest number of occurrences, and   the output unit outputs information based on the product priority and the second recommendation information to the combining unit.   
     
     
         13 . The server according to  claim 7 , wherein
 each piece of recognition information includes a piece of product image information of the product image,   each piece of sales promotion information includes a piece of first sales promotion information relating to sales promotion using the product image,   the analyzing unit analyzes the pieces of purchase information and analyzes the number of occurrences, in the pieces of recognition information, of the piece of product image information associated with the piece of product identification information whose number of occurrences in the pieces of purchase information satisfies a third predetermined condition, and   the analyzing unit obtains, as the updated contents, updated contents of the pieces of first sales promotion information on the basis of the number of occurrences of the piece of product image information.   
     
     
         14 . The server according to  claim 7 , wherein
 each piece of combination information includes an image for combination and a piece of combination image information of the image for combination,   each piece of sales promotion information includes a piece of second sales promotion information relating to sales promotion using the image for combination, and   the analyzing unit analyzes the pieces of purchase information and analyzes the number of occurrences, in the pieces of combination information, of the piece of combination image information associated with the piece of product identification information having a value whose number of occurrences in the pieces of purchase information satisfies a fourth predetermined condition, and   the analyzing unit obtains, as the updated contents, updated contents of the pieces of second sales promotion information on the basis of the number of occurrences of the piece of combination image information.   
     
     
         15 . An analysis method comprising:
 acquiring a piece of recognition information including a piece of product identification information for identifying a product included in a product image;   storing the piece of recognition information in a recognition information storage unit,   acquiring a piece of combination information including the piece of product identification information of the product to be combined with an object image including an object;   storing the piece of combination information in a combination information storage unit;   calculating product priorities for respective products by analyzing a plurality of pieces of recognition information stored in the recognition information storage unit and a plurality of pieces of combination information stored in the combination information storage unit; and   outputting information based on the product priorities.   
     
     
         16 . A computer program product comprising a computer-readable medium containing a program executed by a computer, the program causing the computer to execute:
 acquiring a piece of recognition information including a piece of product identification information for identifying a product included in a product image;   storing the piece of recognition information in a recognition information storage unit,   acquiring a piece of combination information including the piece of product identification information of the product to be combined with an object image including an object;   storing the piece of combination information in a combination information storage unit;   calculating product priorities for respective products by analyzing a plurality of pieces of recognition information stored in the recognition information storage unit and a plurality of pieces of combination information stored in the combination information storage unit; and   outputting information based on the product priorities.