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Insurance Recommendation System

Authors: N. SWAPNA GOUD; B. BHUVANESHWARI; GAYATRI DEEPTHI Y; K. KEERTHANA;

Insurance Recommendation System

Abstract

There is a need for a suitable tool to help people select the right insurance plan because there is a great amount of information about insurance on the internet. By creating a recommendation engine that directly provides a product to its clients, the insurance industry has found a lot of value. Several insurance firms provide various insurance policies. Customers are now unable to decide on a plan because of this. Our invention is creating a suggestion system that is especially tailored for the user. Due to their special characteristics, insurance plans require a different approach than traditional systems. These algorithms often use enormous databases to construct them and aim to suggest the best offer. Our system employs the collaborative filtering technique to determine how likely it is for a user to obtain an insurance plan based on user similarity taking into account their preferences. The usage of recommendation tools is widespread, but little has been done for the insurance sector. Our system uses this technique for insurance suggestions in an effort to close that gap

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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