---
title: "Recommender systems and examples"
subject: "Information System"
chapter: 7
key: "semester_8/information_system:recommender-how-works-examples"
source: https://www.bctengineer.com/q/semester_8/information_system/recommender-how-works-examples
site: BCT Engineering
---

# Recommender systems and examples

Information System · Chapter 7: Web based information system and navigation

- Asked in: 2072 Asoj, 5 marks
- Video: [Recommender System in 6 Minutes](https://www.youtube.com/watch?v=U-yq3I9QugQ) — AI Sciences
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_8/information_system/recommender-how-works-examples
- Whole chapter: https://www.bctengineer.com/md/semester_8/information_system/chapter-7

## Question

What is a recommender system? How does it work? Discuss different examples of recommender systems.

## Short answer

A recommender system filters information to suggest items by collecting user data, building profiles, predicting preferences via content-based or collaborative methods, and ranking top items. Examples: Amazon 'customers also bought', Netflix video suggestions, Spotify Discover Weekly.

## Answer

A **recommender system** is an information filtering system that predicts the preference or rating a user would give to an item and suggests the most relevant items (products, movies, news, friends) to the user. It reduces information overload.

#### How it works
```text
 User data + Item data
        |
   [Collect data]
        |
   [Build profile / model]
        |
   [Find similarity / predict]
        |
   [Rank and recommend top-N]
        |
   [Feedback -> update]
```
1. **Data collection:** explicit ratings and implicit behaviour (clicks, purchases, watch time), item features and user profile.
2. **Learning:** the system builds a user profile and item model.
3. **Prediction:** it uses a technique such as content-based (item similarity to past likes), collaborative filtering (similar users), or hybrid.
4. **Recommendation:** it ranks items and shows the top few.
5. **Feedback:** the user's reactions improve future recommendations.

#### Examples
- **Amazon:** "customers who bought this also bought" (item-based CF).
- **Netflix / YouTube:** recommended videos using watch history and hybrid methods.
- **Spotify:** playlists such as Discover Weekly.
- **Facebook / LinkedIn:** "people you may know".
- **Google News / Daraz:** personalised news and products.
- **Booking sites:** hotels based on previous searches and location.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What does a recommender system do?
   A. Predicts a user's preference and suggests relevant items, reducing information overload
   B. Stores all files of users
   C. Blocks unwanted websites
   D. Compresses data
   Answer: A. It is an information filtering system. (Key point: Definition)

2. What is the correct sequence in how it works?
   A. Recommend, collect data, build model
   B. Rank, delete, collect
   C. Predict, then build data
   D. Collect data, build profile/model, predict, rank and recommend, then update by feedback
   Answer: D. Feedback improves future recommendations. (Key point: Working steps)

3. Which is implicit data?
   A. Star ratings
   B. Written reviews
   C. Clicks, purchases and watch time
   D. Filled profile forms
   Answer: C. Explicit data are ratings and reviews. (Key point: Implicit data)

4. Which is the example of item-based CF in practice?
   A. Spotify top 50
   B. Amazon's 'customers who bought this also bought'
   C. Weather report
   D. Google Maps
   Answer: B. Amazon uses item-based CF. (Key point: Example)

## Related in Information System

- [Recommender system design and types](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Arecommender-design-types) — Information System, chapter 7
- [Generic to personalized recommender](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Arecommender-generic-to-personalized) — Information System, chapter 7
- [Enterprise systems architecture](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Aenterprise-systems-architecture-motivation) — Information System, chapter 3, asked 2×
- [Traditional IS vs enterprise systems](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Atraditional-is-vs-enterprise-systems) — Information System, chapter 3
- [Knowledge management vs expert systems](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Akm-vs-expert-systems) — Information System, chapter 4

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