A Type-2 Fuzzy Approach to Linguistic Summarization of Data

Niewiadomski, Adam

doi:10.1109/tfuzz.2007.902025

Cited by 72 publications

(38 citation statements)

References 25 publications

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“…Maybe, the work of Niewiadomski [24] should be mentioned here. Niewiadomski introduces the concept of Type-2 linguistic summary where the all linguistic terms in a summary, i.e., linguistic quantifiers and fuzzy predicates in summarizers and qualifiers, may be in general represented using Type-2 fuzzy sets instead of "regular" fuzzy sets.…”

Section: Discussion and Related Workmentioning

confidence: 99%

Towards bipolar linguistic summaries: a novel fuzzy bipolar querying based approach

Dziedzic

Zadrożny

Kacprzyk

2012

2012 IEEE International Conference on Fuzzy Systems

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Abstract-We study the possibility to extend the concept of linguistic data summaries employing the notion of bipolarity. Yager's linguistic summaries may be derived using a fuzzy linguistic querying interface. We look for a similar analogy between bipolar queries and the extended form of linguistic summaries. The general concept of bipolar query, and its special interpretation are recalled, which turns out to be applicable to accomplish our goal. Some preliminary results are presented and possible directions of further research are pointed out.

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Section: Discussion and Related Workmentioning

confidence: 99%

Towards bipolar linguistic summaries: a novel fuzzy bipolar querying based approach

Dziedzic

Zadrożny

Kacprzyk

2012

2012 IEEE International Conference on Fuzzy Systems

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“…In [7], authors proposed the use of hierarchical conceptual clustering process to build the summary at different levels of abstraction obtaining a hierarchical summary to describe the database. Additionally, multidimensional databases [13] and type-2 fuzzy logic [14] have also been used within this context.…”

Section: Linguistic Summarization and Descriptionmentioning

confidence: 99%

Transcribing Debussy's Syrinx dynamics through Linguistic Description: The MUDELD algorithm

Ros

Molina-Solana

Delgado

et al. 2016

Fuzzy Sets and Systems

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“…No matter how knowledgeable or expert someone is, one needs to communicate their ideas to other people in natural language, which introduces the issue of imprecision of the words. This rationale suggests that the subject of linguistic summarization [39,73,116,119] is an important topic for ICWW. How to formulate linguistic summarizations so that they are also a part of ACWW is also an important direction for future research.…”

Section: Advanced Computing With Words: Status Challenges and Futurementioning

confidence: 99%

Advanced Computing with Words: Status and Challenges

Mendel

Rajati

2015

Towards the Future of Fuzzy Logic

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In this chapter, we focus on the status of Advanced Computing with Words (ACWW) and the challenges that it may encounter in the future. First, we elaborate on the notion of Computing with Words (CWW) and its various subareas. Then we present some non-engineering ACWW problems and connect them to more realistic engineering problems, after which we provide a roadmap for solving ACWW problems, and show how the Generalized Extension Principle (GEP) can be used to formulate their solutions. We also propose a syllogistic approach to solving ACWW problems that also uses the Extension Principle but in a different way. Finally, we discuss present and future challenges to ACWW, i.e. we explain what challenges ACWW encounters given the current trend of data abundance and widespread use of Internet for dealing with questions posed in natural languages. Introduction: Computing with Words and Advanced Computing with WordsComputing with Words (CWW or CW) [11,29,34,66,69,70,75,91,104,109,142,144,147,154] was probably conceived as the main area of application of fuzzy logic [132] when the field was originated. It is a methodology of computation whose objects are words rather than numbers, although those words are linked to numbers and classical calculations that can be carried out by computing machinery, via membership functions of fuzzy sets associated with words. To do that, a process called precisiation of meaning [152] is essential, which, in a nutshell, is determining membership functions of the fuzzy sets that model the words. Zadeh distinguishes two subareas for CWW:1. Basic Computing with Words (BCWW), which mainly deals with descriptions of complex systems in terms of fuzzy IF-THEN rules [134]. Soft constraints are generally possibilistic, i.e. they describe (physical) attributes like speed, temperature,

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A Type-2 Fuzzy Approach to Linguistic Summarization of Data

Cited by 72 publications

References 25 publications

Towards bipolar linguistic summaries: a novel fuzzy bipolar querying based approach

Towards bipolar linguistic summaries: a novel fuzzy bipolar querying based approach

Transcribing Debussy's Syrinx dynamics through Linguistic Description: The MUDELD algorithm

Advanced Computing with Words: Status and Challenges

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