Computer Basics

Computer Basics is for newbies or persons who may have been out of school for a few years.

What makes search engines good?

How do Search Engines Work?

Many web pages are excluded from most search engines by policy including the searchable databases mounted on the web, such as library catalogs and article databases. All this material is referred to as the "Invisible Web"

Search engines (SE) searches a database of web pages that built by computer robot programs called spiders and indexed by another computer program. If a web page is never linked from any other page, search engine spiders cannot find it. The only way a brand new page can get into a search engine is for other pages to link to it, or for a human to submit its URL for inclusion. 

What Makes a Search Engine Good?" - a table (PDF file) summarizing useful factors for evaluating search engines.

Comparison Table of SE features

Search Engine Features -- Search features and functions of leading search engines.

Types of Search Engines

Crawler-based Search engines Google is one of search engines which works on the method of crawling the data on web, using an automatic software or a bot and all the data was indexed in an Index file , helping in fast retrieval of results. 

Meta search engines attempt to search several different Web search tools (both search engines and subject directories) with one search. A metasearch engine is a search tool that sends user requests to several other search engines and/or databases and aggregates the results into a single list or displays them according to their source. Metasearch engines enable users to enter search criteria once and access several search engines simultaneously. Popular meta search engines include DogPile (which searches more of the large search engines than any other meta search engine) and Ixquick. (i.e.:

Vertical search engines  searches a specific industry, topic, type of content (e.g., travel, movies, images, blogs, live events), piece of data, geographical location, and so on. It may help to think of vertical search as a search within a particular niche. (i.e. IMDB - The Internet Movie Database)

Google Knowledge Graph

Google Knowledge Graph is based on more than search engine rankings.

  • Content Keywords: Which give and idea of keyword variance in the index and relevance
  • Search Queries: Which give an idea about correlation
  • Number of Impressions: Which give an idea about how well the search engine is able to combine and sync the on page signals with the off-page signals.
  • Landing Pages: This gives us an idea about how well each URL is getting indexed along with proper relevance and the correlation factor.
  • Click-Through Rate: This indicates the success factor of the on-page titles and descriptions of the landing page for that relevant search query.
  • link:
    Offers U.S.Gov't Search and other special searches. Patent search.


  • Claims to have over 8 billion searchable pages.
  • Truncation lets you search by the first few letters of a word.
  • Proximity search lets you find terms NEAR each other or NEXT to each other.
  • Thumbnail page previews.
  • Extensive options for refining and limiting your search.
  • intitle:
    after:[time period]
    before:[time period]
    (For details, click on "Advanced search")



Users have a choice between Internet Explorer (Microsoft), Firefox (Mozilla), Safari (Apple), and Google’s offering, Chrome


What is relevancy ranking?

Google PageRank is a graphical representation of relevancy ranking.

Relevancy ranking is the process of sorting the document results so that those documents which are most likely to be relevant to your query are shown at the top.  The simplest method for this is to show highlighted teasers or dynamic page summaries. This technique displays snippets of the source document in the search results with query terms (or expansion terms) highlighted. If the user can quickly see exactly why the document is retrieved (because, for example, both of the user's terms occur close together within a sentence of the document), this makes it more apparent how the engine is working and provides the user with a greater level of comfort that the engine is behaving rationally.

Second, the user query terms can be highlighted within the document itself. Naturally this is a tricky proposition in the wild and wooly world of the World Wide Web, but it can be done and can help the user to determine exactly why a document was retrieved.
Other search engines will provide explanations such as:

  1. How and why synonyms were added to the query
  2. How and why spelling variations are added to the query (the "Did you mean?" feature), and
  3. Full detailed explanations of how the relevancy score was computed

All of these techniques, if they can be made readily apparent to the end-user, provide elbow-room for search engines to expand what it means to provide "User Understandable Relevancy."