---
title: "Web log mining and WWW mining architecture"
subject: "Data Mining"
chapter: 7
key: "semester_7/data_mining:web-log-mining-architecture"
source: https://www.bctengineer.com/q/semester_7/data_mining/web-log-mining-architecture
site: BCT Engineering
---

# Web log mining and WWW mining architecture

Data Mining · Chapter 7: Advanced Applications

- Asked in: year not given, 2+6 marks
- Video: [Web Usage Mining](https://www.youtube.com/watch?v=pq6UQtXf07s) — Web Mining
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/web-log-mining-architecture
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-7

## Question

What is Web Log Mining? Explain WWW Mining Architecture.

## Short answer

Web log mining discovers user behaviour patterns from web server logs. Its architecture has data collection and preprocessing, pattern discovery using association rules, sequential patterns and clustering, and pattern analysis. Applications include personalisation, site improvement, recommendations and fraud detection.

## Answer

**Web log mining** (the main part of web usage mining) is the discovery of useful patterns of user behaviour from **web server logs**: files that record each request made to a web site (IP address, time stamp, requested URL, status code, bytes transferred, referrer, user agent). It helps in site improvement, personalisation and understanding of customers.

#### WWW mining architecture
```text
Web server logs / content / link data
            |
   [1. Data collection & pre-processing]
      cleaning, user & session identification,
      page-view & path completion
            |
   [2. Pattern discovery]
      association rules, sequential patterns,
      clustering, classification, statistics
            |
   [3. Pattern analysis]
      filtering, OLAP, visualisation
            |
   Useful knowledge: personalisation,
   recommendations, site design, caching
```
1. **Data sources**: server logs, proxy server logs, client-side data (cookies), site content and its hyperlink structure, user profiles and registration data.
2. **Pre-processing**: *data cleaning* (remove image requests, failed requests, robot visits), *user identification* (IP + agent, cookies), *session identification* (a time-out, for example 30 minutes), *path completion* and *formatting* into a form for mining.
3. **Pattern discovery**: apply mining techniques: association rules (pages visited together), sequential patterns (navigation order), clustering of users or pages, classification, and statistical analysis (most visited pages).
4. **Pattern analysis**: remove uninteresting patterns; use queries, OLAP and visualisation to interpret.
5. **Applications**: recommendation and personalisation, web site restructuring, targeted ads, caching and prefetching, fraud and attack detection.

## Check yourself

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

1. What does a web server log record?
   A. Only page text
   B. Each request: IP address, time stamp, URL, status code, bytes, referrer, user agent
   C. Only hyperlinks
   D. Only user passwords
   Answer: B. Logs record request details used to infer user behaviour. (Key point: Definition)

2. Which entries are removed during data cleaning?
   A. Image requests, failed requests and robot visits
   B. All HTML page requests
   C. Requests with time stamps
   D. The user's IP address field
   Answer: A. Cleaning removes irrelevant entries such as images, errors and robots. (Key point: Cleaning)

3. How are sessions commonly identified?
   A. By a time-out, for example 30 minutes
   B. By the page size
   C. By the status code
   D. By hyperlink count
   Answer: A. A gap longer than a time-out splits a user's activity into sessions. (Key point: Session identification)

4. Association rules in pattern discovery find which?
   A. The order of navigation
   B. Pages visited together
   C. The server IP
   D. The most recent page
   Answer: B. Association rules find pages accessed together; sequential patterns find the order. (Key point: Pattern discovery)

## Related in Data Mining

- [Short note: WWW mining](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Awww-mining-note) — Data Mining, chapter 7
- [Web mining, importance and techniques](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aweb-mining-importance-techniques) — Data Mining, chapter 7
- [KDD applied to WWW mining](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Akdd-in-www-mining) — Data Mining, chapter 7
- [Web structure/content/usage mining; privacy](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aweb-structure-content-usage-privacy) — Data Mining, chapter 7
- [Web mining structure and challenges](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Aweb-mining-structure-challenges) — Data Mining, chapter 7
- [Architecture of data mining system](https://www.bctengineer.com/question.md?key=semester_7%2Fdata_mining%3Adm-system-architecture) — Data Mining, chapter 1

## Related in other subjects

- [Web mining importance and types](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Aweb-mining-importance-types) — Information System, chapter 7, asked 3×
- [Web mining with structure mining](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Aweb-mining-structure-mining) — Information System, chapter 7
- [Text mining vs web usage mining](https://www.bctengineer.com/question.md?key=semester_8%2Finformation_system%3Atext-mining-vs-web-usage-mining) — Information System, chapter 7
- [Web architecture and web-tier components](https://www.bctengineer.com/question.md?key=semester_7%2Fweb_technology%3Aweb-architecture-tiers) — Web Technology, chapter 2