Scala Machine Learning Projects by Md. Rezaul Karim

Author:Md. Rezaul Karim [Md. Rezaul Karim]
Language: eng
Format: epub, pdf
Tags: COMPUTERS / Information Technology, COMPUTERS / Natural Language Processing, COMPUTERS / Intelligence (AI) and Semantics
Publisher: Packt
Published: 2018-01-30T08:56:52+00:00

Figure 1: A comparative view of different recommendation systems

Collaborative filtering-based approaches often suffer from three problems—cold start, scalability, and sparsity:

Cold start: Sometimes gets stuck when a large amount of data about users is required for making a more accurate recommendation system.

Scalability: A large amount of computation power is often necessary to calculate recommendations out of a dataset with millions of users and products.

Sparsity: This often happens with a crowd-sourced dataset when a huge number of items are sold on major e-commerce sites. In such a case, active users may rate only a small subset of the items sold—that is, even the most popular items have very few ratings. Accordingly, the user versus items matrix becomes very sparse. In other words, a large-scale sparse matrix cannot be handled.

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