3.1. Fuzzification
The process of transforming crisp values into grades of membership for linguistic terms of fuzzy sets is known as fuzzification [25-26, 28, 45-47]. In this work, linguistic variables are evaluated using both triangular and trapezoidal membership functions and accompanied by degree of membership ranging from 0 to 1. The user data and its distribution is compared with various fuzzification membership functions. The collected user data like time-spent and scrolling-speed resembles triangular and trapezoidal membership functions respectively. Therefore this model utilizes both Triangular and Trapezoidal fuzzifiers for the fuzzification of user data as shown in Eq.1 & 3. Fuzzification of given user data can be performed by opting input parameters into Xaxis (Horizontal line) and representing Y-axis (Vertical line) with the upper limit of the membership function for estimating the degree of membership.