Understanding Search Algorithms
- Search engines use searching algorithms to help users find relevant information on the internet.
- These algorithms analyze web pages and rank them based on their relevance and importance.
How PageRank Works
PageRank is a search algorithm developed by Google that ranks web pages based on the number and quality of links pointing to them.
- Link Analysis:
- PageRank assumes that a page is important if it is linked to by other important pages.
- It treats a link from one page to another as a "vote" of confidence.
- Iterative Calculation:
- PageRank assigns a score to each page, starting with an equal score for all pages.
- The score is updated iteratively based on the scores of pages linking to it.
- Damping Factor:
- To prevent infinite loops, PageRank uses a damping factor (usually around 0.85).
- This factor represents the probability that a user will continue clicking on links.
Example
PageRank Calculation
- Page A is linked by Page B and Page C.
- Page B has a PageRank of 2, and Page C has a PageRank of 1.
- Page A's PageRank is calculated as a combination of these scores, adjusted by the damping factor.
Note
PageRank is not the only factor in search rankings. Modern search engines use hundreds of signals to determine relevance.
How HITS Works
HITS (Hyperlink-Induced Topic Search) is a search algorithm that identifies two types of pages: hubs and authorities.
- Hubs and Authorities:
- Hubs are pages that link to many authoritative pages.
- Authorities are pages that are linked to by many hubs.
- Mutual Reinforcement:
- HITS assigns two scores to each page: a hub score and an authority score.
- These scores are updated iteratively, with hubs boosting authorities and vice versa.
Example
HITS Calculation
- Page A links to Pages B and C.
- Pages B and C are considered authorities, while Page A is a hub.
- The authority scores of B and C increase based on A's hub score, and A's hub score increases based on the authority scores of B and C.
Note
HITS is often used for topic-specific searches, as it focuses on the relationship between hubs and authorities.
Comparing PageRank and HITS
- PageRank:
- Focuses on the overall importance of a page based on incoming links.
- Uses a single score for ranking.
- HITS:
- Differentiates between hubs and authorities.
- Uses two scores for ranking.
Hint
PageRank is more commonly used in general search engines, while HITS is useful for specialized searches.
Computational Thinking in Search Algorithms
- Abstraction: Both algorithms simplify the web into a graph of nodes (pages) and edges (links).
- Decomposition: The problem of ranking pages is broken down into smaller tasks, such as calculating scores and updating them iteratively.
- Pattern Recognition: The algorithms identify patterns in linking behavior to determine importance.
