Information retrieval
Information retrieval is defined as "a branch of computer or library science relating to the storage, locating, searching, and selecting, upon demand, relevant data on a given subject."[1] As noted by Carl Sagan, "human beings have, in the most recent few tenths of a percent of our existence, invented not only extra-genetic but also extrasomatic knowledge: information stored outside our bodies, of which writing is the most notable example."[2] The benefits of enhancing personal knowledge with retrieval of extrasomatic knowledge has been shown in a controlled comparison with rote memory.[3]
Although information retrieval is usually thought of being done by computer, retrieval can also be done by humans for other humans.[4]
Classification
Information retrieval can be divided into information discovery, information recovery, and information awareness.[5]
Information discovery
Information discovery is searching for information that the searcher has not seen before and the searcher does not know for sure that the information exists. Information discovery includes searching in order to answer a question at hand, or searching for a topic without a specific question in order to improve knowledge of a topic.
Information recovery
Information recovery is searching for information that the searcher has seen before and knows to exist.
Information awareness
Information awareness has also been described as "'systematic serendipity' - an organized process of information discovery of that which he [the searcher] did not know existed".[5] Examples of this prior to the Internet include reading print and online periodicals. With the Internet, new methods include email newsletters[6], email alerts, and RSS feeds.[7]
Factors associated with successful retrieval
Characteristics of how the information is stored
For storage of text content, the quality of the index to the content is important. For example, the use of stemming, or truncating, words by removing suffixes may help.[8]
Display of information
Information that is structured was found to be more effective in a controlled study.[2] In addition, the structure should be layered with a summary of the content being the first layer that the readers sees.[9] This allows the reader to take only an overview, or choose more detail.
Characteristics of the search engine
John Battelle has described features of the perfect search engine of the future.[10] For example, the use of Boolean searching may not be as efficient.[11]
Characteristics of the searcher
In healthcare, searchers are more likely to be successful if their answer is answer before searching, they have experience with the system they are searching, and they have a high spatial visualization score.[12] Also in healthcare, physicians with less experience are more likely to want more information.[13] Physicians who report stress when uncertain are more likely to search textbooks than source evidence.[14]
In healthcare, using expert searchers on behalf of physicians led to increased satisfaction by the physicians with the search results.[15]
References
- ↑ National Library of Medicine. Information Storage and Retrieval. Retrieved on 2007-12-12.
- ↑ 2.0 2.1 Sagan, Carl. Dragons of Eden. [New York: Ballantine Books. ISBN 0-345-34629-7.
- ↑ de Bliek R, Friedman CP, Wildemuth BM, Martz JM, Twarog RG, File D (1994). "Information retrieved from a database and the augmentation of personal knowledge". J Am Med Inform Assoc 1 (4): 328–38. PMID 7719819. [e]
- ↑ Mulvaney, S. A., Bickman, L., Giuse, N. B., Lambert, E. W., Sathe, N. A., & Jerome, R. N. (2008). A randomized effectiveness trial of a clinical informatics consult service: impact on evidence-based decision-making and knowledge implementation, J Am Med Inform Assoc, 15(2), 203-211. doi: 10.1197/jamia.M2461.
- ↑ 5.0 5.1 Garfield, E. “ISI Eases Scientists’ Information Problems: Provides Convenient Orderly Access to Literature,” Karger Gazette No. 13, pg. 2 (March 1966). Reprinted as “The Who and Why of ISI,” Current Contents No. 13, pages 5-6 (March 5, 1969), which was reprinted in Essays of an Information Scientist, Volume 1: ISI Press, pages 33-37 (1977). http://www.garfield.library.upenn.edu/essays/V1p033y1962-73.pdf
- ↑ Roland M. Grad et al., “Impact of Research-based Synopses Delivered as Daily email: A Prospective Observational Study,” J Am Med Inform Assoc (December 20, 2007), http://www.jamia.org/cgi/content/abstract/M2563v1 (accessed December 21, 2007).
- ↑ Algorithms Are Terrific. But to Search Smarter, Find a Person. Retrieved on 2008-04-04.
- ↑ Porter MF. An algorithm for suffix stripping. Program. 1980;14:130–7.
- ↑ Writing Inverted Pyramids in Cyberspace (Alertbox). Retrieved on 2007-12-12.
- ↑ John Battelle. The Search: How Google and Its Rivals Rewrote the Rules of Business and Transformed Our Culture. Portfolio Trade. ISBN 1-59184-141-0.
- ↑ Verhoeff, J (2001). Inefficiency of the use of Boolean functions for information retrieval system. Communications of the ACM. 1961;4:557 DOI:10.1145/366853.366861
- ↑ Hersh WR, Crabtree MK, Hickam DH, et al (2002). "Factors associated with success in searching MEDLINE and applying evidence to answer clinical questions". J Am Med Inform Assoc 9 (3): 283–93. PMID 11971889. [e]
- ↑ Gruppen LD, Wolf FM, Van Voorhees C, Stross JK (1988). "The influence of general and case-related experience on primary care treatment decision making". Arch. Intern. Med. 148 (12): 2657–63. PMID 3196128. [e]
- ↑ McKibbon KA, Fridsma DB, Crowley RS (2007). "How primary care physicians' attitudes toward risk and uncertainty affect their use of electronic information resources". J Med Libr Assoc 95 (2): 138–46, e49–50. DOI:10.3163/1536-5050.95.2.138. PMID 17443246. Research Blogging.
- ↑ Shelagh A. Mulvaney et al., “A Randomized Effectiveness Trial of a Clinical Informatics Consult Service: Impact on Evidence Based Decision-Making and Knowledge Implementation,” J Am Med Inform Assoc (December 20, 2007), http://www.jamia.org/cgi/content/abstract/M2461v1 (accessed December 21, 2007).