Information Retrieval on the

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A critical factor in the success of the web is the ability to find information on it. Search technology is an important area of research.

To retrieve information on the WWW, one may enter a query into a broad-based search engine such as Google or Yahoo, or one may issue a query at a particular website or portal. A site or search engine may allow queries in natural language (such as a question, ''What is the altitude of Mount Kilimanjaro?'') or as a series of keywords that may or may not be grouped (e.g., 'Sonoran Desert' vs. 'Sonoran' 'Desert' vs. inclusion of Boolean logic ('Sonoran AND desert')).

Search engines maintain an index that lists words and the addresses where they are used. The index is created using a crawler, or a program that follows links in hypertext documents, building an index of the words it finds in the documents. Query terms can then be matched to this index to quickly locate relevant resources which are termed the search results.

A variety of different algorithms exist to find, rank, and categorize search results. In some fields of life sciences, there are specialized searches such as BLAST, in which a genetic sequence is input and similar sequences stored in GenBank are output. Specialized ecological search algorithms are likely to emerge as more ecological data become digitally available.

Many sites offer advanced searching to allow users to narrow or filter searches interactively using a form customized for their data model, or database schema. Some sites organize information into taxonomies that are displayed in hierarchical lists, or as graphical representations that can be explored by browsing as well as by searching. One such visualization tool is University of Vermont's GrOWL (Figure 3).

Figure 3 GrOWL knowledge map for the Ecosystem Services Database. This Java-based viewer was developed at the University of Vermont Ecoinformatics Collaboratory using the TouchGraph visualization engine. It provides a way to interactively and graphically explore related concepts in the ontology for the Ecosystems Services Database. A right click on a concept provides a way to search the database for material relevant to that concept. Screenshot from http://esd.uvm.edu, reproduced with permission.

Figure 3 GrOWL knowledge map for the Ecosystem Services Database. This Java-based viewer was developed at the University of Vermont Ecoinformatics Collaboratory using the TouchGraph visualization engine. It provides a way to interactively and graphically explore related concepts in the ontology for the Ecosystems Services Database. A right click on a concept provides a way to search the database for material relevant to that concept. Screenshot from http://esd.uvm.edu, reproduced with permission.

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