A Personalized Recommendation Technique for Travel Route Based on Fuzzy Consistent Matrix

Recommending travel routes for tourists has become a research hotspot in the present tourism industry. Various machine learning methods have been well studied recommendation systems. However, accuracy of these systems is not up to expected levels. In order increase ranking accuracy, as as, recall rate recommended by personalized algorithm, this paper, fuzzy consistent matrix technique introduced First all, user’s interest data are obtained through consistency matrix. Next, de-noised determine preferred points and coverage points. Besides this, constraints route also topic. Therefore, proposed method uses technology users’ similarity classifies algorithm. Finally, model constructed comprehend recommendation. The investigational outcomes, using real datasets, illustrate that when number 5000, then approximately 97.21%, 97.54%. We observed 60 GB data, method, routes, can reach high 97.59%.