SUMMARY
In the decision support method with analytic hierarchy process (AHP), each evaluation criteria are evaluated for target objective, and each alternative is evaluated for each evaluation criteria. This method recommends alternatives to the user according to the total degree of weight, which is calculated from these two kinds of evaluation values. If the target user does not know all alternatives, AHP needs to use the average value of other evaluators’ evaluation in usual decision support method. However, this method does not reflect target user's preference, and the result does not satisfy the user in many cases. This paper proposes a decision support method with AHP according to similar preference. The proposal method searches the set of alternatives evaluation by others, which is nearest to evaluation by target user in the evaluation distance between alternatives. Evaluation distance is calculated using the value of an evaluation level. The shorter distance the set of alternatives is, the more appropriate alternatives user finds in this method. In practical experiment, the proposal method recommended more satisfied alternatives than the usual method, in which the evaluation value of alternatives is the average value among other evaluators.
Analytic hierarchy process (AHP) is an effective method for product recommendation, because each evaluation criteria are evaluated for target objective, and each alternative are evaluated for each evaluation criteria. This method recommends alternatives to the user according to the total degrees of weight, which is calculated from these 2 kinds of evaluation values. The determination of weight is hard work, because of many evaluations. This paper proposes a product recommendation system with AHP according to Normalization allocation and Hough conversion in order to evaluate alternatives.Normalization allocation can calculate automatically the evaluation value of the alternatives for every criterion. Hough conversion can extract the number of straight line elements from the target image. Through the experiment, it is confirm that the proposal system can recommend alternatives as well as the conventional system. K E Y W O R D S AHP (Analytic Hierarchy Process), alternatives, Hough conversion, normalization allocation, product recommendation Electron Comm Jpn. 2019;102:25-41.
Analytic hierarchy process (AHP) is an effective method for product recommendation, because each evaluation criteria are evaluated for target objective, and each alternative are evaluated for each evaluation criteria. This method recommends alternatives to the user according to the total degrees of weight, which is calculated from these 2 kinds of evaluation values. The determination of weight is hard work, because of many evaluations. This paper proposes a product recommendation system with AHP according to Normalization allocation and Hough conversion in order to evaluate alternatives.Normalization allocation can calculate automatically the evaluation value of the alternatives for every criterion. Hough conversion can extract the number of straight line elements from the target image. Through the experiment, it is confirm that the proposal system can recommend alternatives as well as the conventional system. K E Y W O R D S AHP (Analytic Hierarchy Process), alternatives, Hough conversion, normalization allocation, product recommendation Electron Comm Jpn. 2019;102:25-41.
The analytic hierarchy process (AHP) is an effective method for product selection support because it evaluates alternatives based on the total weight, which is a quantitative value. The total weight is obtained by multiplying the ratio of each evaluation criterion for the target user and the weights of alternatives in each evaluation criterion.The determination of weights in the qualitative evaluation criterion is difficult because of the necessity to compare the questionnaire results of all alternatives. This article proposes Decision Support System for Product Selection based on AHP, using the decision rule of Rough Set for Qualitative Evaluation. The proposed system makes decision rules based on the target user's judgment of "Good" or "Bad" on several samples in the qualitative evaluation criterion. Decision rules have a qualitative and quantitative evaluation value for each attribute, and the system calculates the weight of the AHP through normalization of these evaluation values. The user can know the results easily because the evaluation method of alternative samples in the proposed system is the same as that of correspondence with the shop assistant in an actual store. Based on two experiments, we confirm that the setup of attributes for decision rules of rough sets is one of the most important elements of the proposed system.
K E Y W O R D Sanalytic hierarchy process, alternative, decision rule, decision support system for product selection, qualitative evaluation, rough conversion Electron Comm Jpn. 2019;102:15-29.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.