The Internet: How Search Works

Code.org
13 Jun 201705:12

Summary

TLDRThis script delves into the inner workings of search engines, emphasizing the responsibility they hold in providing accurate answers to a diverse range of queries. It explains how search engines use spiders to index the web and algorithms, like Google's PageRank, to rank results. The script also touches on the challenges of spam and the evolution of search engines to understand context and meaning through machine learning, ensuring that relevant information remains easily accessible.

Takeaways

  • 🔍 Search engines are continuously scanning the web in advance to provide faster search results, rather than searching in real-time.
  • 🕷️ A 'Spider' program is used to crawl web pages and collect information, which is then stored in a search index.
  • 📚 When a search is performed, the engine looks for the query terms in the search index to generate a list of relevant web pages.
  • 🤔 Search engines use algorithms to rank pages, guessing what the user is looking for based on various factors like the presence of search terms in the page title.
  • 🔑 Google's PageRank algorithm determines the relevance of pages by considering the number of other web pages linking to a given page.
  • 🛡️ Search engines regularly update their algorithms to combat spam and ensure that untrustworthy sites do not rank highly.
  • 👀 Users should remain vigilant and check the reliability of sources by examining web addresses.
  • 📈 Modern search engines use machine learning to understand the context and meaning of words beyond just their presence on a page.
  • 📍 Search engines can provide personalized results, such as showing nearby dog parks even if the user's location was not specified.
  • 🧠 Machine learning allows search algorithms to understand the underlying meaning of words, distinguishing between different uses, like 'fast pitcher' for an athlete versus 'large pitcher' for a kitchen item.
  • 🌐 Despite the exponential growth of the internet, effective search engine design aims to keep relevant information easily accessible.

Q & A

  • Who is John and what is his role at Google?

    -John is the leader of the search and machine learning teams at Google, responsible for providing the best answers to users' search queries.

  • What is Akshaya's position and her team's focus at Bing?

    -Akshaya works on the Bing search team, focusing on the integration of artificial intelligence and machine learning to make an impact on society.

  • Why doesn't a search engine search the web in real time when a user makes a query?

    -Searching the web in real time would be too slow due to the vast number of websites. Instead, search engines use pre-indexed information to provide faster results.

  • What is the role of a Spider in a search engine's operation?

    -A Spider is a program that crawls through web pages, following hyperlinks and collecting information to be stored in a search index for future searches.

  • How does a search engine determine the most relevant results for a user's query?

    -Search engines use algorithms to rank pages based on various factors, such as the presence of search terms in the page title or the proximity of words, to determine the most relevant results.

  • What is the PageRank algorithm, and who is it named after?

    -PageRank is Google's algorithm for ranking search results based on the number of other web pages that link to a given page. It is named after its inventor, Larry Page, a founder of Google.

  • Why do search engines need to regularly update their algorithms?

    -Search engines update their algorithms to prevent spammers from manipulating search results and to ensure that fake or untrustworthy sites do not appear at the top of search results.

  • How can users identify untrustworthy pages in search results?

    -Users can identify untrustworthy pages by examining the web address and ensuring it comes from a reliable source.

  • How do modern search engines use information not explicitly provided by the user to improve search results?

    -Modern search engines use location data and other contextual information to provide more personalized and relevant results, such as showing nearby dog parks even if the user did not specify their location.

  • What role does machine learning play in improving search engine results?

    -Machine learning helps search engines understand the underlying meaning of words on a page, allowing them to provide more accurate and contextually relevant results.

  • How does the exponential growth of the internet affect the design of search engines?

    -The design of search engines must evolve to handle the exponential growth of the internet, ensuring that the information users want can still be quickly and easily accessed.

Outlines

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Mindmap

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Keywords

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Highlights

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Transcripts

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Etiquetas Relacionadas
Search EnginesArtificial IntelligenceMachine LearningPageRank AlgorithmInternet SpeedWeb IndexingSEOGoogleBingOnline Algorithms
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