Information retrieval

Introduction edit

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. Information retrieval is the science^[1] of searching for information in a document, searching for documents themselves, and also searching for the metadata that describes data, and for databases of texts, images or sounds.

Automated information retrieval systems are used to reduce what has been called information overload. An IR system is a software system that provides access to books, journals and other documents; it also stores and manages those documents. Web search engines are the most visible IR applications.

Learning Tasks edit

(Information Systems) Explore the learning resource about Information Systems and identify the links between different information systems and information retrieval.
(Mathematical Foundations) Explain, how mathematics can be used to handle
- search requests,
- how to represent knowledge
(Web Crawler) What is web crawler and why is it necessary to rely on web crawlers to create e.g. an web index to handle search requests of users.

Learning Modules edit

Overview edit

An information retrieval process begins when a user enters a query into the system. Queries are formal statements of information needs, for example search strings in web search engines. In information retrieval, a query does not uniquely identify a single object in the collection. Instead, several objects may match the query, perhaps with different degrees of relevance.

An object is an entity that is represented by information in a content collection or database. User queries are matched against the database information. However, as opposed to classical SQL queries of a database, in information retrieval the results returned may or may not match the query, so results are typically ranked. This ranking of results is a key difference of information retrieval searching compared to database searching.^[2]

Depending on the application the data objects may be, for example, text documents, images,^[3] audio,^[4] mind maps^[5] or videos. Often the documents themselves are not kept or stored directly in the IR system, but are instead represented in the system by document surrogates or metadata.

Most IR systems compute a numeric score on how well each object in the database matches the query, and rank the objects according to this value. The top ranking objects are then shown to the user. The process may then be iterated if the user wishes to refine the query.^[6]

Applications edit

Areas where information retrieval techniques are employed include (the entries are in alphabetical order within each category):

General applications edit

Digital libraries
Information filtering
- Recommender systems
Media search
- Blog search
- Image retrieval
- 3D retrieval
- Music retrieval
- News search
- Speech retrieval
- Video retrieval
Search engines

Domain-specific applications edit

Expert search finding
Genomic information retrieval
Geographic information retrieval
Information retrieval for chemical structures
Information retrieval in software engineering
Legal information retrieval
Vertical search

Other retrieval methods edit

Methods/Techniques in which information retrieval techniques are employed include:

Major conferences edit

Awards in the field edit

References edit

↑ Luk, R. W. P. (2022). "Why is information retrieval a scientific discipline?". Foundations of Science 27 (2): 427–453. doi:10.1007/s10699-020-09685-x.
↑ Jansen, B. J. and Rieh, S. (2010) The Seventeen Theoretical Constructs of Information Searching and Information Retrieval Archived 2016-03-04 at the Wayback Machine. Journal of the American Society for Information Sciences and Technology. 61(8), 1517-1534.
↑ Goodrum, Abby A. (2000). "Image Information Retrieval: An Overview of Current Research". Informing Science 3 (2).
↑ Foote, Jonathan (1999). "An overview of audio information retrieval". Multimedia Systems 7: 2–10. doi:10.1007/s005300050106.
↑ Beel, Jöran; Gipp, Bela; Stiller, Jan-Olaf (2009). Information Retrieval On Mind Maps - What Could It Be Good For?. Proceedings of the 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'09). Washington, DC: IEEE. Archived from the original on 2011-05-13. Retrieved 2012-03-13.
↑ Frakes, William B.; Baeza-Yates, Ricardo (1992). Information Retrieval Data Structures & Algorithms. Prentice-Hall, Inc.. ISBN 978-0-13-463837-9. https://www.scribd.com/doc/13742235/Information-Retrieval-Data-Structures-Algorithms-William-B-Frakes.

External links edit

Search Wikiquote for quotations related to: Information retrieval

Page Information edit

This page was based on the following wikipedia-source page:

[luk22-1] Luk, R. W. P. (2022). "Why is information retrieval a scientific discipline?". Foundations of Science 27 (2): 427–453. doi:10.1007/s10699-020-09685-x.

[2] Jansen, B. J. and Rieh, S. (2010) The Seventeen Theoretical Constructs of Information Searching and Information Retrieval Archived 2016-03-04 at the Wayback Machine. Journal of the American Society for Information Sciences and Technology. 61(8), 1517-1534.

[goodron2000-3] Goodrum, Abby A. (2000). "Image Information Retrieval: An Overview of Current Research". Informing Science 3 (2).

[Foote99-4] Foote, Jonathan (1999). "An overview of audio information retrieval". Multimedia Systems 7: 2–10. doi:10.1007/s005300050106.

[Beel2009-5] Beel, Jöran; Gipp, Bela; Stiller, Jan-Olaf (2009). Information Retrieval On Mind Maps - What Could It Be Good For?. Proceedings of the 5th International Conference on Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom'09). Washington, DC: IEEE. Archived from the original on 2011-05-13. Retrieved 2012-03-13.

[Frakes1992-6] Frakes, William B.; Baeza-Yates, Ricardo (1992). Information Retrieval Data Structures & Algorithms. Prentice-Hall, Inc.. ISBN 978-0-13-463837-9. https://www.scribd.com/doc/13742235/Information-Retrieval-Data-Structures-Algorithms-William-B-Frakes.

[1]

[2]

[3]

[4]

[5]

[6]