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Software Recommendation using Frequent Pattern Growth Algorithm and Web Usage Mining

Author: 
Vijay Prakash Tiwari, Akshay Bapusaheb Patil, Vikas Tiwari, Dhruvesh Chudasama and Avinash Murlidhar Ingole,
Subject Area: 
Physical Sciences and Engineering
Abstract: 

In this ever-evolving generation, Technological advancements are having exponential growth. People try to learn new thing and technological enthusiastic are always in pursuit to learn about the new technologies. Since Learning and Researching about Technologies is also an ever-going process in an individual life span therefore there comes a time where one might stand in ambiguity and questions what to learn next or what to pursue next. Other person’s recommendations are always has been a prior option but in today world mostly one isn’t available every time to others. To help in such situation we need an AI based Recommendation System that would analyses various parameters of available information and eventually would suggest the best probable technology for the person. Recommendation system would provide the detail information and recommend that software to the user. Analyzing the trends, interests and popularity of the technology in the market combined with the individual’s activities recommendation system should recommend the next software to be learned. This would just not only help in the ever-going learning process but also make people up to date about recent technological trends so the quality of innovation and invention can be improved to greater extent. Such Recommendation System would also allow the various product and service based organization to introduce their innovative product on the platform and can help them to popularize their very potential product in the market among the technological enthusiasts.

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