Popularly used recommendation for product is very important, also creating association among them serves with best recommendation. In this work FP Growth is used which calculates scores for final recommendation. Different approaches are used for dealing with different keywords to suggest recommendation. Efficient recommendation can be provided by creating relationships between associated books. Recommendation system recommend items and products depending on user`s interest and preferences. The proposed recommendation system for books is based on calculating scores and frequency by using opinion mining and sentimental analysis.

Opinion Mining, FP Growth, Recommendation System, Sentimental Analysis.

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