Search Enter text
Knowledge Management Glossary
51. Parsing: In natural language processing, detecting the structure of groups of words, according to Ask Jeeves.com, http://www.jeevessolutions.com/technology/natural_language.asp
52. Pilot: A complete trial of a system, but on a limited basis in terms of the targeted user group.
53. Prototype: A model on which something is patterned. In software development, most often demonstrating "proof of concept," in other words, proving the conceptual basis of the software. However, this usually means the conceptual basis of the interface rather than the conceptual basis of the operation of the whole software program.
54. Question-type: Defining the main information required by a type of query in advance, according to Jose Luis Vicedo and Antonio Ferrández in "A semantic approach to Question Answering systems," http://trec.nist.gov/pubs/trec9/papers/alicante_trec_9_paper.pdf
55. Scalability: The ability of a computer application, hardware, or system to function just as effectively at another size or volume, typically larger, according to what is.com http://search390.techtarget.com/sDefinition/0,,sid10_gci212940,00.html
56. Scale: The ability to exhibit scalability. Please see scalability.
57. Semantic Analysis: In natural language processing, matching words and structures to meanings, according to Ask Jeeves.com, http://www.jeevessolutions.com/technology/natural_language.asp
58. Set-match Criteria:The development of profile points that permits the matching of found groups of points to the profile in conducting a search.
59. Statistical Processing: Search conducted by means of classifying information by tracking the number of times certain words and phrases are used. Sometimes sophisticated algorithms that search for the proximity of words are used in conjunction with statistical processing.
60. Stemming: In natural language processing, identifying the base forms of words, according to Ask Jeeves.com, http://www.jeevessolutions.com/technology/natural_language.asp
61. Stop-wording: Eliminating commonly occurring words like on, it, at, this, there, and so on, and pure verbs (words which are verbs only), e.g., calculate, listen, and so on, in order to eliminate high-frequency words that are too general to be useful in processing a NLP search or in data mining.
62. Tag: To tag is to put a descriptor on a software language element in order to describe it.
63. Tokenization: In natural language processing, dividing a string of characters into linguistically salient units, according to Ask Jeeves.com, http://www.jeevessolutions.com/technology/natural_language.asp
64. Trigger: A mechanism that starts an action when an event occurs. Something that causes a program routine to be executed, according to www.atomica.com. (See the complete definition via Atomica, particularly the interesting references to database management and intelligent databases.)
Home | The Course | Case Studies | Discussion |Glossary
About Us | Help | Previous Work | KM Links