@article{oai:omu.repo.nii.ac.jp:00000897,
 author = {MORITA, Hiroyuki and NAKAHARA, Takanobu},
 journal = {Journal of economics, business and law},
 month = {Mar},
 note = {application/pdf, Data mining is utilized in a variety of commercial and other real-world applications. The subject data are not only numerical, but also character, text, and image data. Of these, image data are the most difficult to mine directly for effective information or knowledge. After digitizing image data, we can apply various mining methods to them. In this paper, we propose a method to mine useful information from photographs. Using photographs of various foods, our objective is to identify the factors (such as lighting, shape, or color) that give people the impress that the food in the image must be delicious. After we identify some useful explanatory variables using the KeyGraph, we extract these variables from photographs by using genetic algorithms and analyze them with regression analysis. The results confirmed that an image of food can be made more appetizing by increasing the size of the food domain (that is, the part of the image occupied by the food itself) relative to the whole image and by using large numbers of red pixels while avoiding the use of blue pixels., Journal of economics, business and law. 2005, 7, p.73-85},
 pages = {73--85},
 title = {Data mining from photographs using the KeyGraph and genetic algorithms},
 volume = {7},
 year = {2005}
}