Prediction of User Future Request Utilizing the Combination of Both ANN and FCM in Web Page Recommendation

This paper explains about the web page recommendation system. This procedure encompasses consumers’ upcoming demand and web page recommendations. In the proposed web page recommendation system, potential and non-potential data can be categorized by use of the Levenberg–Marquardt firefly neural network algorithm, and forecast can be made by using the K-means clustering algorithm. Consequently, the projected representation demonstrates the infrequent contact format with the help of the representation that integrates the comparable consumer access model data that belong to the further consumer. Thereafter, the impending user data are specified to the clustering progression. The third phase of the projected process is collecting potential data with the aid of the improved fuzzy C-means clustering algorithm. The last step of our projected process is envisaging the upcoming demand for the subsequent consumer. The presentation of the projected procedure will be compared to the obtainable procedure.

Abstract licence: CC BY

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