A COOPERATIVE WEB RECOMMENDATION SYSTEM THAT USES THE HIDDEN MARKOV MODEL

SEEE DIGIBOOK ON ENGINEERING & TECHNOLOGY, VOL. 01 (2), JUN 2020 PP. (809-812)
Abstract– In a short period of time, the World Wide Web has become one of the most comprehensive information databases available. It provides nearly all of the necessary details for each user. On the other hand, locating information on a massive website is not simple. The majority of website users struggle with gaining timely access to the information they need. Finding the essential dataset on the internet is one of the most challenging and time-consuming tasks of the modern era. The exponential growth of the Internet in recent years necessitates the development of more user- friendly recommender systems in online applications. Collaborative filtering (CF) technologies, which predict a user’s personal preference based on the user’s past actions, have become one of the most effective methods for developing modern recommender systems. Using an improved version of a new, more efficient algorithm for web recommendation systems based on the Hidden Markov Model, it is possible to identify users who provide false ratings to an online image system.
Index Terms – Hidden Markov Model, Recommendation System, Collaborative filtering.
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Mehala G, Ananthi P, Ganeshkumar G
Department of Computer Science and Engineering,
Rathinam Technical Campus, Coimbatore, India

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