An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

Today, various stakeholders provide a large number of functionally similarWeb Services (WS) to meet increasingly complex business needs. Therefore, distinguish similar WS, some researchers have proposed using the non-functional characteristics, named Quality Service (QoS), and user’s needs, expressed through Experience (QoE). Thus, all those QoS QoE attributes should be taken into account in predicting WS quality jointly, called QoSE (Quality Experience). However, these are different nature, i.e., is data-driven numerical, while expert-based linguistic. Consequently, predict QoSE, this paper, we propose hybrid fuzzy inference approach, composing both quantitative qualitative data inputs output by applying adaptive neuro-fuzzy system (ANFIS). The developed prototype allows us implement investigate its performance, study effect on QoSE. results two experiments show good performance suitability approach for based combining attributes. We expect that inspire practitioners understand better develop user needs matching WS.