scholarly journals Universal and macro-areal patterns in the lexicon

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Thanasis Georgakopoulos ◽  
Eitan Grossman ◽  
Dmitry Nikolaev ◽  
Stéphane Polis

Abstract This paper investigates universal and areal structures in the lexicon as manifested by colexification patterns in the semantic domains of perception and cognition, based on data from both small and large datasets. Using several methods, including weighted semantic maps, formal concept lattices, correlation analysis, and dimensionality reduction, we identify colexification patterns in the domains in question and evaluate the extent to which these patterns are specific to particular areas. This paper contributes to the methodology of investigating areal patterns in the lexicon, and identifies a number of cross-linguistic regularities and of area-specific properties in the structuring of lexicons.

2020 ◽  
Vol 196 ◽  
pp. 105777
Author(s):  
Jadson Jose Monteiro Oliveira ◽  
Robson Leonardo Ferreira Cordeiro

Author(s):  
Cassio Melo ◽  
Bénédicte Le-Grand ◽  
Marie-Aude Aufaure

Browsing concept lattices from Formal Concept Analysis (FCA) becomes a problem as the number of concepts can grow significantly with the number of objects and attributes. Interpreting the lattice through direct graph-based visualisation of the Hasse diagram rapidly becomes difficult and more synthetic representations are needed. In this work the authors propose an approach to simplify concept lattices by extracting and visualising trees derived from them. The authors further simplify the browse-able trees with two reduction methods: fault-tolerance and concept clustering.


2020 ◽  
Vol 39 (3) ◽  
pp. 2783-2790
Author(s):  
Qian Hu ◽  
Ke-Yun Qin

The construction of concept lattices is an important research topic in formal concept analysis. Inspired by multi-granularity rough sets, multi-granularity formal concept analysis has become a new hot research issue. This paper mainly studies the construction methods of concept lattices in multi-granularity formal context. The relationships between concept forming operators under different granularity are discussed. The mutual transformation methods of formal concepts under different granularity are presented. In addition, the approaches of obtaining coarse-granularity concept lattice by fine-granularity concept lattice and fine-granularity concept lattice by coarse-granularity concept lattice are examined. The related algorithms for generating concept lattices are proposed. The practicability of the method is illustrated by an example.


Information ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 78 ◽  
Author(s):  
Jingpu Zhang ◽  
Ronghui Liu ◽  
Ligeng Zou ◽  
Licheng Zeng

Formal concept analysis has proven to be a very effective method for data analysis and rule extraction, but how to build formal concept lattices is a difficult and hot topic. In this paper, an efficient and rapid incremental concept lattice construction algorithm is proposed. The algorithm, named FastAddExtent, is seen as a modification of AddIntent in which we improve two fundamental procedures, including fixing the covering relation and searching the canonical generator. The proposed algorithm can locate the desired concept quickly by adding data fields to every concept. The algorithm is depicted in detail, using a formal context to show how the new algorithm works and discussing time and space complexity issues. We also present an experimental evaluation of its performance and comparison with AddExtent. Experimental results show that the FastAddExtent algorithm can improve efficiency compared with the primitive AddExtent algorithm.


2014 ◽  
Vol 36 (5) ◽  
pp. S111-S131 ◽  
Author(s):  
Haim Avron ◽  
Christos Boutsidis ◽  
Sivan Toledo ◽  
Anastasios Zouzias

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