Encyclopedia of Computer Science and Technology

information theory 241the question into the structured queries most likely to elicitdocuments containing the answer. Ask Jeeves (retired as of2006) and similar search services have thus far been onlymodestly successful with this approach.On a large scale, systematic information retrieval andanalysis (see data mining) has become increasingly sophisticated,with applications ranging from e-commerce andscientific data analysis to counterterrorism. Artificial intelligencetechniques (see pattern recognition) play animportant role in cutting-edge systems.Finally, encoding more information about content andstructure within the document itself can provide moreaccurate and useful retrieval. The use of XML and worktoward a “semantic Web” offers hope in that direction (seeBerners-Lee, Tim; semantic web; and xml).A number of criteria can be used by Web search engines to determinethe likely relevance of search results. Perhaps the most importanttool, however, is feedback from the user.pared to one another). There is also more likelihood thatsearchers will either make syntax errors in their requests orcreate requests that do not have the intended effect.While database systems can control the organizationof data, the pathways for retrieval and the command setor interface, the World Wide Web is a different matter.It amounts to the world’s largest database—or perhapsa “metabase” that includes not only text pages but fileresources and links to many traditional database systems.While the flexibility of linkage is one of the Web’s strengths,it makes the construction of search engines difficult. Withmillions of new pages being created each week, the “webcrawler”software that automatically traverses links andrecords and indexes site information is hard pressed tocapture more than a diminishing fraction of the availablecontent. Even so, the number of “hits” is often unwieldy(see search engine).A number of strategies can be used to provide morefocused search results. The title or full text of a given pagecan be checked for synonyms or other ideas often associatedwith the keyword or phrase used in the search. Themore such matches are found, the higher the degree ofrelevance assigned to the document. Results can then bepresented in declining order of relevance score. The usercan also be asked to indicate a result document that he orshe believes to be particularly relevant. The contents of thisdocument can then be compared to the other result documentsto find the most similar ones, which are presented aslikely to be of interest to the researcher.Information retrieval from either stand-alone databasesor the Web can also be improved by making it unnecessaryfor users to employ structured query languages (see sql)or even carefully selected keywords. Users can simply typein their request in the form of a question, using ordinarylanguage: For example, “What country in Europe has thelargest population?” The search engine can then translateFurther ReadingBell, Suzanne S. Librarian’s Guide to Online Searching. Westport,Conn.: Libraries Unlimited, 2006.Chakrabarti, Soumen. Mining the Web: Discovering Knowledge fromHypertext Data. San Francisco: Morgan Kaufmann, 2002.Grossman, David A., and Ophir Frieder. Information Retrieval:Algorithms and Heuristics. 2nd ed. Norwell, Mass.: Springer,2004.“Information Retrieval Research.” Search Tools Consulting. Availableonline. URL: http://www.searchtools.com/info/inforetrieval.html.Accessed August 8, 2007.Meadow, Charles T., et al. Text Information Retrieval Systems. 3rded. Burlington, Mass.: Academic Press, 2007.information theoryInformation theory is the study of the fundamental characteristicsof information and its transmission and reception.As a discipline, information theory took its impetus fromthe ideas of Claude Shannon (see Shannon, Claude).In his seminal paper “A Mathematical Theory of Communication”published in the Bell System Technical Journalin 1948, Shannon analyzed the redundancy inherent in anyform of communication other than a series of purely randomnumbers. Because of this redundancy, the amount ofinformation (expressed in binary bits) needed to convey amessage will be less than the number in the original message.It is because of redundancy that data compressionalgorithms can be applied to text, graphics, and other typesof files to be stored on disk or transmitted over a network(see data compression).Shannon also analyzed the unpredictability or uncertaintyof information as it is received—that is, the number ofpossibilities for the next bit or character. This is related to thenumber of possible symbols, but since all symbols are usuallynot equally likely, it is actually a sum of probabilities. Shannonused the physics term entropy to refer to this measure. Itis important because it makes it possible to analyze the probabilityof error (caused by such things as “line noise”) in acommunications circuit. Shannon’s basic formula is:C = Blog 2 (1 + P / N)where the channel capacity C is in bits per second, B is thebandwidth, P the signal power, and N the Gaussian noisepower.