Discovery system

Artificial intelligence

• Autoclass
• Automated Mathematician
• DALTON
• Eurisko
• Glauber
• Machine for Questions and Answers
• Stahl

  Bibliographical search system

Typical features of a discovery system

• Large search space: A search can search the data from different data sources. For example, you can search a journal article or a textbook directly in the discovery system and you do not have to change from a subject database to the library catalog.
• Intuitive usability, like a search engine. The search is basically only a simple form, an advanced search function is not always provided.
• Ranking of the results according to relevance: The "best" hit is displayed first, not necessarily the newest one. A good ranking is important because many hits are often found due to the large search space.
• Search refinement with drill-down menus : For example, a search can be restricted to all matches available online.
• Correction of input errors via a "Did you mean ...?" function.
• Autocomplete: After input to the search field, a drop-down list of suggestions appears.
• Exploratory search: One finds results of interest that were not specifically requested. For example, links to similar hits, entries in subject databases, or Wikipedia articles are displayed.

  Examples of discovery system products

• Summon
• Primo Central
• EBSCO Discovery Service
• WorldCat Discovery

• VuFind
• Lukida