Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

A Survey on Web Usage Mining

Now a day World Wide Web become very popular and interactive for transferring of information. The web is huge, diverse and active and thus increases the scalability, multimedia data and temporal matters. The growth of the web has outcome in a huge amount of information that is now freely offered for user access. The several kinds of data have to be handled and organized in a manner that they can be accessed by several users effectively and efficiently. So the usage of data mining methods and knowledge discovery on the web is now on the spotlight of a boosting number of researchers. Web usage mining is a kind of data mining method that can be useful in recommending the web usage patterns with the help of users2019; session and behavior. Web usage mining includes three process, namely, preprocessing, pattern discovery and pattern analysis. There are different techniques already exists for web usage mining. Those existing techniques have their own advantages and disadvantages. This paper presents a survey on some of the existing web usage mining techniques

Implicative and conjunctive fuzzy rules: A tool for reasoning from knowledge and examples

Fuzzy rule-based systems have been mainly used as a convenient tool for synthesizing control laws from data. Recently, in a knowledge representation-oriented perspective, a typology of fuzzy rules has been laid bare, by emphasizing the distinction between implicative and conjunctive fuzzy rules. The former describe pieces of generic knowledge either tainted with uncertainty or tolerant to similarity, while the latter encode examples-originated information expressing either mere possibilities or how typical situations can be extrapolated. The different types of fuzzy rules are first contrasted, and their representation discussed in the framework of possibility theory. Then, the paper studies the conjoint use of fuzzy rules expressing knowledge (as fuzzy constraints which restrict the possible states of the world), or gathering examples (which testify the possibility of appearance of some states). Coherence and inference issues are briefly addressed

A comparison of techniques for learning and using mathematics and a study of their relationship to logical principles

Various techniques exist for learning mathematical concepts, like experimentation and exploration, respectively using mathematics, like modelling and simulation. For a clear application of such techniques in mathematics education, there should be a clear distinction between these techniques. A recently developed theory of fuzzy concepts can be applied to analyse the four mentioned concepts. For all four techniques one can pose the question of their relationship to deduction, induction and abduction as logical principles. An empirical study was conducted with 12-13 aged students, aiming at checking the three reasoning processes

“Almost Identical with Itself” : A Search for a Logic of Fuzzy Identity

This thesis grows out of a fascination with the vagueness of natural language, its manifestation in the ancient Sorites paradox, and the way in which the paradox is dealt with in fuzzy logic. It is an attempt to resolve the tension between two versions of the paradox, and the related problem of whether identity can be fuzzy. If it can be fuzzy, then the most popular argument against vague objects is mistaken, which would be great news for those who hold that there can be vagueness in the world independently of our representation or knowledge of it. The standard Sorites is made up of conditionals about an ordinary predicate (e.g. “heap”) by the rule of modus ponens. It is typically solved in fuzzy logic by interpreting the predicate as a fuzzy relation and showing that the argument fails as a result. There is another, less known version of the paradox, based on the identity predicate and the rule of substitutivity of identicals. The strong analogy between the two versions suggests that their solutions might be analogical as well, which would make identity just as vague as any relation. Yet the idea of vague identity has traditionally been rejected on both formal and philosophical grounds. Even Nicholas J. J. Smith, who is known for his positive attitude toward fuzzy relations in general, denies that identity could be fuzzy. The opposite position is taken by Graham Priest, who argues for a fuzzy interpretation of identity as a similarity relation. Following Priest, I aim to show that there is a perfectly sensible logic of fuzzy identity and that a fuzzy theoretician of vagueness therefore cannot rule out fuzzy identity on logical grounds alone. I compare two fuzzy solutions to the identity Sorites: Priest’s solution, based on the notion of local validity, and B. Jack Copeland’s solution, based on the failure of contraction in sequent calculus. I provide a synthesis of the two solutions, suggesting that Priest’s local validity counts as a genuine kind of validity even if he might not think so himself. The substitutivity of identicals is not locally valid in Priest’s logic, however; his solution only applies to a special case with the rule of transitivity. Applying L. Valverde’s representation theorem and other mathematical results, I lay the foundation for a stronger logic where the substitutivity rule is locally valid and the two Sorites merge into one paradox with one solution. Finally, I defend fuzzy identity against Gareth Evans’ argument that vague identity leads to contradiction, and Smith’s argument that vague identity is not really identity. The former relies on a fallacious application of the substitutivity rule; to the latter, my principal response is to question Smith’s understanding of identity and argue for a broader one. I conclude that not only is fuzzy identity logically possible, but it also has potential applicability in metaphysics and elsewhere

An Ensemble Classification and Hybrid Feature Selection Approach for Fake News Stance Detection

The developments in Internet and notions of social media have revolutionised representations and disseminations of news. News spreads quickly while costing less in social media. Amidst these quick distributions, dangerous or seductive information like user generated false news also spread equally. on social media. Distinguishing true incidents from false news strips create key challenges. Prior to sending the feature vectors to the classifier, it was suggested in this study effort to use dimensionality reduction approaches to do so. These methods would not significantly affect the result, though. Furthermore, utilising dimensionality reduction techniques significantly reduces the time needed to complete a forecast. This paper presents a hybrid feature selection method to overcome the above mentioned issues. The classifications of fake news are based on ensembles which identify connections between stories and headlines of news items. Initially, data is pre-processed to transform unstructured data into structures for ease of processing. In the second step, unidentified qualities of false news from diverse connections amongst news articles are extracted utilising PCA (Principal Component Analysis). For the feature reduction procedure, the third step uses FPSO (Fuzzy Particle Swarm Optimization) to select features. To efficiently understand how news items are represented and spot bogus news, this study creates ELMs (Ensemble Learning Models). This study obtained a dataset from Kaggle to create the reasoning. In this study, four assessment metrics have been used to evaluate performances of classifying models