Searching the Deep Web Winter 2012 Virtual Parking Lot If you should have questions that are either too time consuming theoretical or technical in nature to be addressed ID: 782390
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Ryerson University Library and Archives Searching the Deep Web Winter 2012
Slide2Virtual Parking LotIf you should have questions that areeither too time consuming, theoretical or technical in nature to be addressedin this introductory session, then e-mail your question to Jay Wolofsky jwolofsk@ryerson.ca… the answer to your question(s) will beshared with the group.
Slide3The Deep Web The Deep Web is currently 400 to 500 times larger than the commonly defined Surface Web or WWW (7,500 terabytes of information compared to 19 terabytes of information in the Surface Web and is growing exponentially
Slide4Deep Web/Surface Web The Deep Web (a.k.a.) the Invisible Web contains high quality information not accessible from conventional conventional search engines such as Google
Slide5Deep Web/Surface Web Structured information contained in research databases cannot be accessed from the Surface Web
Slide6Deep Web/Surface WebThe real problem is the spidering and crawling technology used by conventional search engines that return links based on popularity, not contentSurface Web search results are ranked by the Frequency documents link to each other (page rank)The first results are those that have had the most references by other documents, and not necessarilythe most relevant or recent Information or content
Slide7Federated Search Engines \ Federated search engines execute simultaneous real time search of the Deep Web using sophisticated software “connectors”
The results are collated and presented back to the user in a unified format
Slide8Federated Search Engines One type, a ‘web spider variant’ crawls information from from as many databases as possible creating a giant uniform index, e.g. Google Scholar A more advanced type searches across each database’s own indexing AND crawls information, e.g., Biznar, Mednar, DeepDyve
Slide9Federated Search EnginesThere are 3 general types: The first type searches across each database using its own indexing The second type ‘web spider’ crawls Information from as many databases as possible creating a giant uniform index, e.g. Google Scholar, OpenDOARThe third type searches across each database’s own indexing AND crawls information, e.g. Biznar, Mednar, DeepDyve …
Slide10Accessing Deep Web ContentBiznar (Business)DeepDyve (Multidisciplinary)E-Print Network (Science and Technology)Google Scholar (Multidisciplinary)Highbeam (Multidisciplinary)HighWire (Multidisciplinary)Mednar (Medicine)MetaPress (Multidisciplinary)OpenDOAR (Multidisciplinary)Science.gov (Science and Technology)Scirus (Science and Technology)Social Science Research Network (Social Sciences)World Wide Science
(Science and Technology)