• DocumentCode
    856237
  • Title

    Search: postscript ...and shall ye find?

  • Author

    Edwards, Chris

  • Volume
    3
  • Issue
    11
  • fYear
    2008
  • Firstpage
    64
  • Lastpage
    64
  • Abstract
    In this paper, Web search engine is discussed. At the core of most search engines is the concept of word frequency: words that pop-up more regularly in a document tend to score more highly in rankings when a user searches. However, there are common words that are found frequently in lots of documents. Words like those are not very useful in finding the document you want. Microsoft´s Live search engine combines a number of techniques which are combined using a neural network. This neural network is meant to learn how techniques can best be combined to deliver what users want to find. There are other machine-learning approaches now in use. Some search-engine builders, such as autonomy, have gone back to probabilistic techniques, but in place of frequency have used algorithms that allow the machine to learn how text is structured statistically. These engines use Bayesian inference to process the text: computing the probability of one word following another.
  • Keywords
    belief networks; inference mechanisms; search engines; text analysis; word processing; Bayesian inference; Microsofts live search engine; machine learning approach; neural network; text processing; word frequency;
  • fLanguage
    English
  • Journal_Title
    Engineering & Technology
  • Publisher
    iet
  • ISSN
    1750-9637
  • Type

    jour

  • Filename
    4621896