Reinterpreting Interpretability for Fuzzy Linguistic Descriptions of Data

被引：4
|
作者：
Ramos-Soto, A. [1 ,2 ]
Pereira-Farina, M. [3 ,4 ]
机构：
[1] Univ Santiago de Compostela, Ctr Singular Invest Tecnol Informac CiTIUS, Rua Jenaro de la Fuente Dominguez, Santiago De Compostela, Spain
[2] Univ Aberdeen, Dept Comp Sci, Aberdeen, Scotland
[3] Univ Santiago de Compostela, Dept Filosofia & Antropol, Santiago, Spain
[4] Univ Dundee, Ctr Argument Technol ARG Tech, Dundee, Scotland
来源：
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS: THEORY AND FOUNDATIONS, IPMU 2018, PT I | 2018年 / 853卷
关键词：
Fuzzy sets; Linguistic summarization; Interpretability; Data-to-text; Fuzzy linguistic descriptions of data; Natural language generation; GENERATION; MECHANISM;
D O I：
10.1007/978-3-319-91473-2_4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We approach the problem of interpretability for fuzzy linguistic descriptions of data from a natural language generation perspective. For this, first we review the current state of linguistic descriptions of data and their use contexts as a standalone tool and as part of a natural language generation system. Then, we discuss the standard approach to interpretability for linguistic descriptions and introduce our complementary proposal, which describes the elements from linguistic descriptions of data that can influence and improve the interpretability of automatically generated texts (such as fuzzy properties, quantifiers, and truth degrees), when linguistic descriptions are used to determine relevant content within a text generation system.
引用
收藏
页码：40 / 51
页数：12
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