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2. Information retrieval - Wikipedia

   en.wikipedia.org/wiki/Information_retrieval

   Information retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an information need. The information need can be specified in the form of a search query. In the case of document retrieval, queries can be based on full-text or other content-based indexing.

3. Ranking (information retrieval) - Wikipedia

   en.wikipedia.org/.../Ranking_(information_retrieval)

   Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.

4. Document management system - Wikipedia

   en.wikipedia.org/wiki/Document_management_system

   Document management systems may have a rights management module that allows an administrator to give access to documents based on type to only certain people or groups of people. Document marking at the time of printing or PDF-creation is an essential element to preclude alteration or unintended use. Workflow.

5. Document retrieval - Wikipedia

   en.wikipedia.org/wiki/Document_retrieval

   Document retrieval is defined as the matching of some stated user query against a set of free-text records. These records could be any type of mainly unstructured text, such as newspaper articles, real estate records or paragraphs in a manual. User queries can range from multi-sentence full descriptions of an information need to a few words.

6. Okapi BM25 - Wikipedia

   en.wikipedia.org/wiki/Okapi_BM25

   Okapi BM25. In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson, Karen Spärck Jones, and others.

7. List of academic databases and search engines - Wikipedia

   en.wikipedia.org/wiki/List_of_academic_databases...

   Users need to account for qualities and limitations of databases and search engines, especially those searching systematically for records such as in systematic reviews or meta-analyses. [2] As the distinction between a database and a search engine is unclear for these complex document retrieval systems, see: