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About Content - Based Recommender Systems
This document outlines some of the key challenges faced by content-based recommender systems (CBRS), including limited content analysis and overspecialization of recommendations. It discusses how CBRS work by creating user profiles based on item ratings and comparing those profiles to item content descriptions. However, representing items and profiles with only keywords can fail to capture important semantics and multi-word concepts. The document also examines strategies for addressing CBRS's tendency to only recommend similar, obvious items rather than surprising or serendipitous recommendations.
Detailed Information
| Author: | ['ramadevi'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 89 |
| Language: | English |
| Format: | |
| Price: | FREE |
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