People write reviews of numerous products or services on the Internet, in their blogs or community bulletin boards. These unstructured data contain important emotions and opinions about the author's product or service, which can provide important information for future product design or marketing. However, this text-based information cannot be evaluated quantitatively, and thus they are difficult to apply to mathematical models or optimization problems for product design and improvement. Therefore, this study proposes a method to quantitatively extract user’s opinion or preference about a specific product or service by utilizing a lot of text-based information existing on the Internet or online. The extracted unstructured text information is decomposed into basic unit words, and positive rate is evaluated by using existing emotional dictionaries and additional lists proposed in this study. This can be a way to effectively utilize unstructured text data, which is being generated and stored in vast quantities, in product or service design. Finally, to verify the effectiveness of the proposed method, a case study was conducted using movie review data retrieved from a portal website. By comparing the positive rates calculated by the proposed framework with user ratings for movies, a guideline on text mining based evaluation of unstructured data is provided.

This research had been conducted from May to October 2007, studying 110 residents of G, Y, H industrial area in Jun-nam province. It is designed to understand the difference in levels of indoor, outdoor and personal exposure to VOCs(benzene, toluene, Ethylbenzene) and a health risk assessment was conducted to see if there was any fatal cause from carcinogenic or non - carcinogenic elements from a case group and a control group in all areas as well as each different area. In the case of benzene in the air, the geometric levels for the case group are indoor, outdoor and personal exposure; a higher than for the control group. As a results of the Monte - Carlo study about benzene, it shows that the case group’s carcinogenicity is higher than that of the control group and it also shows that, on the CTE, RME condition and Monte - Carlo analysis, all subjects are seen to exceed the carcinogenicity tolerance 10-6 of US EPA. In the case of toluene, ethylbenzene on the CTE, RME condition and Monte - Carlo analysis, these do not exceed the non - carcinogenic standard of 1, but toluene in RME condition for both groups’ personal exposure and the indoor and personal exposure of ethylbenzene in Monte - Carlo show that these seem to exceed the standard.