Self-Organisation of Conceptual Spaces from Quality Dimensions

2015 ◽  
pp. 141-163 ◽  
Author(s):  
Paul Vogt
Keyword(s):  
Conceptual Spaces ◽  
Quality Dimensions ◽  
Self Organisation

Representing wine concepts: A hybrid approach

2020 ◽  
Vol 15 (4) ◽  
pp. 475-491
Author(s):  
M. Cristina Amoretti ◽  
Marcello Frixione
Keyword(s):  
Hybrid Approach ◽  
Sufficient Conditions ◽  
Geometric Representation ◽  
Conceptual Spaces ◽  
Geographical Indication ◽  
Knowledge Based ◽  
Quality Dimensions ◽  
Grape Varieties ◽  
Degree Of Similarity ◽  
Representation Of Knowledge

Wines with geographical indication can be classified and represented by such features as designations of origin, producers, vintage years, alcoholic strength, and grape varieties; these features allow us to define wines in terms of a set of necessary and/or sufficient conditions. However, wines can also be identified by other characteristics, involving their look, smell, and taste; in this case, it is hard to define wines in terms of necessary and/or sufficient conditions, as wine concepts exhibit typicality effects. This is a setback for the design of computer science ontologies aiming to represent wine concepts, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. To solve this problem, we propose to adopt a hybrid approach in which ontology-oriented formalisms are combined with a geometric representation of knowledge based on conceptual spaces. As in conceptual spaces, concepts are identified in terms of a number of quality dimensions. In order to determine those relevant for wine representation, we use the terminology developed by the Italian Association of Sommeliers to describe wines. This will allow us to understand typicality effects about wines, determine prototypes and better exemplars, and measure the degree of similarity between different wines.

scholarly journals Hierarchical Linear Disentanglement of Data-Driven Conceptual Spaces

2020 ◽  
Author(s):  
Rana Alshaikh ◽  
Zied Bouraoui ◽  
Steven Schockaert
Keyword(s):  
Vector Space ◽  
Representation Learning ◽  
Data Driven ◽  
Vector Spaces ◽  
Conceptual Spaces ◽  
Semantic Features ◽  
Geometric Meaning ◽  
Domain Specific ◽  
Text Corpora ◽  
Quality Dimensions

Conceptual spaces are geometric meaning representations in which similar entities are represented by similar vectors. They are widely used in cognitive science, but there has been relatively little work on learning such representations from data. In particular, while standard representation learning methods can be used to induce vector space embeddings from text corpora, these differ from conceptual spaces in two crucial ways. First, the dimensions of a conceptual space correspond to salient semantic features, known as quality dimensions, whereas the dimensions of learned vector space embeddings typically lack any clear interpretation. This has been partially addressed in previous work, which has shown that it is possible to identify directions in learned vector spaces which capture semantic features. Second, conceptual spaces are normally organised into a set of domains, each of which is associated with a separate vector space. In contrast, learned embeddings represent all entities in a single vector space. Our hypothesis in this paper is that such single-space representations are sub-optimal for learning quality dimensions, due to the fact that semantic features are often only relevant to a subset of the entities. We show that this issue can be mitigated by identifying features in a hierarchical fashion. Intuitively, the top-level features split the vector space into different domains, making it possible to subsequently identify domain-specific quality dimensions.

scholarly journals Data-driven Conceptual Spaces: Creating Semantic Representations For Linguistic Descriptions Of Numerical Data

2018 ◽  
Vol 63 ◽  
pp. 691-742 ◽  
Author(s):  
Hadi Banaee ◽  
Erik Schaffernicht ◽  
Amy Loutfi
Keyword(s):  
A Priori ◽  
Empirical Evaluation ◽  
Numerical Data ◽  
Semantic Interpretation ◽  
Data Driven ◽  
Conceptual Spaces ◽  
Semantic Features ◽  
Semantic Representations ◽  
Quality Dimensions ◽  
Using Data

There is an increasing need to derive semantics from real-world observations to facilitate natural information sharing between machine and human. Conceptual spaces theory is a possible approach and has been proposed as mid-level representation between symbolic and sub-symbolic representations, whereby concepts are represented in a geometrical space that is characterised by a number of quality dimensions. Currently, much of the work has demonstrated how conceptual spaces are created in a knowledge-driven manner, relying on prior knowledge to form concepts and identify quality dimensions. This paper presents a method to create semantic representations using data-driven conceptual spaces which are then used to derive linguistic descriptions of numerical data. Our contribution is a principled approach to automatically construct a conceptual space from a set of known observations wherein the quality dimensions and domains are not known a priori. This novelty of the approach is the ability to select and group semantic features to discriminate between concepts in a data-driven manner while preserving the semantic interpretation that is needed to infer linguistic descriptions for interaction with humans. Two data sets representing leaf images and time series signals are used to evaluate the method. An empirical evaluation for each case study assesses how well linguistic descriptions generated from the conceptual spaces identify unknown observations. Furthermore, comparisons are made with descriptions derived on alternative approaches for generating semantic models.

The effect of gravity on microtubule self-organisation

2001 ◽  
Vol 11 (PR6) ◽  
pp. Pr6-239-Pr6-246 ◽  
Author(s):  
J. Tabony ◽  
N. Glade ◽  
C. Papaseit ◽  
J. Demongeot
Keyword(s):  
Self Organisation

The Effect of Service Quality on Customers' Satisfaction in Mobile Phone Services in the UAE

2020 ◽  
Vol 8 (1) ◽  
pp. 75-94
Author(s):  
Emad Yusuf Masoud
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Mobile Phone ◽  
Service Providers ◽  
Mobile Service ◽  
Behavioural Difference ◽  
Mobile Industry ◽  
Quality Dimensions ◽  
Service Quality Dimensions ◽  
Network Quality

This study aims to determine the dimensions of mobile service quality and to examine their effect on customer satisfaction in UAE mobile phone service providers while also investigating the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. A combination of the SERVPERF model has been adopted as the main framework for analyzing service quality. A structured questionnaire instrument was designed for data collection. The present study concentrates on the level of customers’ satisfaction for leading service providers in the UAE mobile industry. Etisalat and Du were chosen for this study. A sample of (452) mobile phone users in Abu Dhabi city was selected at random using convenience-sampling. We found a positive effect of both functional and technical service quality (network quality) on customers’ satisfaction. Functional and technical dimensions were good predictors of customer satisfaction and confirmed the multidimensional nature of service quality. Also, the service quality dimensions; reliability, assurances, and responsiveness are found to be significant predictors of customer satisfaction. Behavioural difference between mobile phone customers is also significant in predicting customer satisfaction for postpaid subscribers. However, only reliability and network quality are significant predictors of customer satisfaction for prepaid subscribers. The model developed in this study provides marketers and researchers with a diagnostic tool to assess service quality from the perspectives of customers to meet the customer’s expectations and ensure customer satisfaction.

The Prospects and Risks Connected with Increasing the Level of Self-Organisation in Students

2020 ◽  
pp. 75-81
Author(s):  
Svetlana Alexandrovna Kosareva ◽  
Keyword(s):  
Higher Education ◽  
Professional Competence ◽  
Initial Level ◽  
Education Institution ◽  
Diagnostic Methods ◽  
Study Guide ◽  
Learning Approaches ◽  
Control Groups ◽  
Self Organisation ◽  
And Control

The paper describes the method for increasing the level of self-organisation in students which has been developed by the author. It also contains the method testing results and presents the prospects and risks teachers could face while applying the method in a higher education institution. The purpose of this study is to find out the prospects and risks of applying the method for increasing the level of self-organisation in students and to determine the ways of reducing the risks. Methodology. The author points out the learning approaches which were the basis of developing the method and describes diagnostic methods for determining students’ self-organisation levels. The work focused on increasing each student’s initial level consists of a theoretical and a practical part and includes project activities on creating a study guide. The results of the study. The method developed proved to be effective. It was established by diagnosing the final level of self-organisation in students in the experimental and control groups. The paper considers the advantages of the method among which there is universal character, flexibility, improvements to teacher’s and students’ professional competence, etc. At the same time it is necessary to be aware of the risks due to the increased amount of teacher’s work and the fact that students’ work within the project tends to be monotonous. In conclusion, the prospects of the method for increasing the level of self-organisation in students are related to its advantages and the final results of the work. The risks of its use can be reduced with the help of the measures proposed in the paper.

Die Eigen-Werte der Literatur

2009 ◽  
Vol 54 (1) ◽  
pp. 103-119
Author(s):  
Matthias Bickenbach
Keyword(s):  
The Self ◽  
Literary Writing ◽  
Self Organisation ◽  
Insight Into

Eine der zentralen Fragen moderner Poetik ist, wie der Werkentstehungsprozeß von kreativer Materialfülle zur ästhetischen Bestimmtheit des Erzählten als autonomem Kunstwerk übergeht. Sten Nadolnys Poetikvorlesung gibt überraschende Einsichten in die Selbstorganisation von Steuerungsbewegungen, die noch unterhalb der Ebene des Schreibens liegen und die als Theorie der Eigenwerte in der Literatur herauszustellen ist. One of the central questions in modern poetics is, how literary writing proceeds from the creative richness of its material to an aesthetic determination as autonomous art. Sten Nadolnys lectures on his poetics enable an astonishing insight into the self-organisation of operations beyond writing, which can be considered as a theory of self-values in literature.

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