Collaborative Filtering Model - PDF

Collaborative Filtering Model
via Contractive Auto-encoders

Introduction:
The following presentation demonstrates
Collaborative Filtering or CF. It is helpful to provide users
with various personalized services and products.
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• Further, this leverages the side information of items and
users that has been extensively researched here to
develop performance.
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• To deal with the rising sparseness of the user-item
matrix, it has been still remaining in challenge.
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• In order to tackle such issue, the hybrid kind of CF like
assimilation with filtering that is content based is used.
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• Further with the rise in number of online information the
recommender system has been playing with more
indispensable role.
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• Moreover, it has been boosting the sales for
organizations under e-commerce.
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• The user preference of CF is studied that has been
extending from usage patterns like user-item
interactions for making recommendations.
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