Information search and retrieval theory has focused on the problem of precision vs. recall. Recall refers to how much information is retrieved by the search. Precision refers to the reliability of the information, the relevant number of documents retrieved. The goal of IR scientists is to provide the most precise or relevant documents in the midst of the recalled search results.
Thesauri, subject headings, and keywords searching have been the customary strategies used for location of materials. Categorizing by subject or descriptor term creates a thesaurus of specified terms, a controlled vocabulary.
Searching this list identifies cataloged items. However, new computing techniques--artificial intelligence, natural language processing, relevancy feedback, query-by-example, and concept-based searching--have added a new sophistication to information retrieval. Robots, computers that search the Web using these new techniques (aka spiders or wanderers) offer the 'net searcher a higher degree of precision in retrieval.
The presentation is targeted toward Web searchers, in particular, reference librarians and those who navigate the Internet on a frequent basis. This presentation will look at search engines, comparing search techniques and noting differences. The workshop will identify use of new computing techniques for IR within each engine.