Data Mining via Protoform Based Linguistic Summaries: Some Possible Relations to Natural Language Generation

被引:8
|
作者
Kacprzyk, Janusz [1 ]
Zadrozny, Slawomir [1 ]
机构
[1] Polish Acad Sci, Syst Res Inst, PL-01447 Warsaw, Poland
关键词
FUZZY ASSOCIATION RULES; QUANTIFIERS;
D O I
10.1109/CIDM.2009.4938652
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Linguistic database summaries in the sense of Yager (1982), further extended to an implementable form by Kacprzyk & Yager (2001) and Kacprzyk, Yager & Zadrozny (2000), are extremely simple natural language like statements exemplified by, for a personnel database, "most employees are young and well paid" (with some degree of truth). They have been implemented in business contexts (cf. Kacprzyk & Zadroiny, ????, Kacprzyk, Wilbik and Zadrozny, 2006-2008). An effective and efficient way of their generation was proposed by Kacprzyk & Zadroiny (????) by using an interactive procedure based on Kacprzyk & Zadrozny's (????) fuzz), database queries with linguistic quantifiers. Moreover, in Kacprzyk & Zadroiny (???) the role of Zadeh's (???) protoform was shown and their use advocated. Though linguistic database summaries have a strong resemblance to natural language generation (NLG), this issue was never considered. In this paper we indicate some important issues that are common to linguistic database summarization and natural language generation, and propose some possible research directions.
引用
收藏
页码:217 / 224
页数:8
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