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Learning Bit by Bit Search. Information Retrieval Census Memex Sea of Documents Find those related to “new media” Brute force.

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Presentation on theme: "Learning Bit by Bit Search. Information Retrieval Census Memex Sea of Documents Find those related to “new media” Brute force."— Presentation transcript:

1 Learning Bit by Bit Search

2 Information Retrieval Census Memex Sea of Documents Find those related to “new media” Brute force

3 The Internet Search Engines

4 Anatomy of a Search Engine Crawler Indexer Query Matcher

5 Crawling Process 1.Seeding 2.Run: a. Check for Exit Criteria b. Retrieve Content c. Extract URLs d. Determine next URL

6 Seeding Initial Set of URLs

7 Exit Criteria When to stop: – Threshold of pages met – Time period – No more URLs

8 Retrieve Content Read the page Optionally determine if it is relevant

9 Extract URLs Depth check ie. 5 Content is parsed for hyperlinks

10 Invisible webpages robots.txt sitemaps

11 Determine Next URL

12 Breadth first Weighted search: – Authority

13 Demo Simple Crawler on nytimes.com

14 Indexing Lucene, etc.

15 Queries Avoid spam Find the best answer

16 Link Analysis/Pagerank Citations Hyperlinks as recommendations

17 Link Analysis/Pagerank j-> i nytimes.commoma.org nytimes.com01/3 moma.org1/100 Links to page j / number outlinks from page i ex. nytimes.com has 3 outlinks 1 of which is to moma.org moma.org has 10 outlinks 1 of which is to nytimes.com

18 Precision vs. Recall Recall – percentage of relevant documents returned by the algorithm – True positives / true positives + false negatives Precision – percentage of returned documents the user finds relevant – True positives / true positives + false positives

19 Demos Spam avoidance with pagerank Scaling up search with nutch


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