A Research Project Proposal
Table of Contents
1. Introduction
We all use Google, Bing, DuckDuckGo, and other search engines. They are part of daily life, but most people never think about what happens between pressing “Enter” and getting results in under a second. Most users treat search engines like a magic eight ball: you ask a question, and an answer appears. But behind that simple interaction is one of the most complex engineering systems ever built. It has to crawl billions of web pages, index them, rank them, and serve the most useful results.
This research project aims to explain how that process works. Instead of treating search engines as black boxes, we will look at the main parts that make them work: crawling, indexing, ranking and query processing. We will also look at how these parts fit together to create a seemless end product. The goal is not just to describe what search engines do, but to understand how and why they do it.
2. Main Question
How do search engines transform a user’s query into a ranked list of relevant results, and what are the technical and algorithmic considerations involved in that process?
2.1 Subquestions
- How does web crawling work, and how do search engines decide what to crawl and how often?
- What is an inverted index, and how does it enable fast retrieval across billions of documents?
- Which options exist for indexing and how to they compare?
- How do ranking algorithms (e.g., PageRank) determine relevance and authority?
- How are queries parsed, expanded, and matched against the index?
- How do different substitute algorithms compare to eachother
- How can AI be integrated into search engines, and at which point are they more efficient than traditional algorithms?
3. Methodology
This project will combine literature review, case study analysis, and small-scale practical experimentation.
- Literature review: Survey foundational papers (e.g., Brin & Page’s original PageRank paper, modern learning-to-rank literature) and technical documentation from search providers.
- Case studies: Compare the architectures and stated philosophies of big existing search engines.
- Practical component: Build a miniature search engine over a small corpus (e.g., a set of Wikipedia articles) to demonstrate crawling, indexing, and ranking in action.
4. Expectations
By the end of this project, I expect to:
- Have a clear, technically grounded understanding of each major stage of search engine operation.
- Be able to explain the trade-offs between speed, relevance, cost, and privacy.
- Have a working (if small) demonstration of crawling, indexing, and ranking.
5. Conclusion
Search engines are one of the most important technologies that helped shaped the internet today. They provide the information people find, believe, and act on. But most users don’t really know how they work. This project aims to change that, not by taking apart any one search engine, but by explaining the basic principles and technical backbones that all of them share. The goal is to give a clearer picture of the impressive engineering behind the modern search engine.
Note: This is a working proposal and will be revised as research progresses.