Natural Language and its Ontology

This paper gives a characterization of the ontology implicit in natural language and the entities it involves, situates natural language ontology within metaphysics, and responds to Chomskys' dismissal of externalist semantics

Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks

Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles

On The Very Importance Of The Metaphoric As Semantic To Communication, Understanding, And The Philosophy Of Language

The focus of this thesis is a defense of metaphorical meaning. Since metaphor is such a fundamental aspect of language, my first emphasis is to find error in pragmatic theories of meaning. The first two chapters are where this occurs; in chapter one, we first investigate an account of intention and convention as developed by Grice, Lewis, and others, ultimately leading to our rejection of it. The second chapter is similar in structure, but rather investigates Searle’s account of regulative rules. The third chapter refutes those positions that reject the possibility of metaphorical meaning, i.e., that consider it a ‘pragmatic’ phenomenon (one that is determined by use rather than meaning). Tbat chapter also investigates the issue of language as context-independent, the possibility of a metaphor as paraphrasable, and the question of ‘dead metaphor.’ The fourth chapter, consequently, aims at presenting a positive account of metaphorical meaning. My claim is that not only does metaphor have meaning, but that all meaning is to some extent metaphorical. We will also determine why we use metaphor and what, in my view, a dead metaphor really is. The final chapter is designed to give a preliminary account of what a theory of understanding compatible with metaphor would look like and explores views outside of analytic philosophy

Effective Knowledge Transfer: A Terminological Perspective - Dismantling The Jargon Barrier To Knowledge About Computer Security

The research is concerned with the terminological problems that computer users experience when they try to formulate their knowledge needs and attempt to access information contained in computer manuals or online help systems while building up their knowledge. This is the recognized but unresolved problem of communication between the specialist and the layman. The initial hypothesis was that computer users, through their knowledge of language, have some prior knowledge of the subdomain of computing they are trying to come to terms with, and that language can be a facilitating mechanism, or an obstacle, in the development of that knowledge. Related to this is the supposition that users have a conceptual apparatus based on both theoretical knowledge and experience of the world, and of several domains of special reference related to the environment in which they operate. The theoretical argument was developed by exploring the relationship between knowledge and language, and considering the efficacy of terms as agents of special subject knowledge representation. Having charted in a systematic way the territory of knowledge sources and types, we were able to establish that there are many aspects of knowledge which cannot be represented by terms. This submission is important, as it leads to the realization that significant elements of knowledge are being disregarded in retrieval systems because they are normally expressed by language elements which do not enjoy the status of terms. Furthermore, we introduced the notion of `linguistic ease of retrieval' as a challenge to more conventional thinking which focuses on retrieval results

Linguistic Deviation in Literary Style

This paper is an attempt to shed light on linguistic deviation in literary style. Literary language, with its three main genres; poetry, drama and prose, is a situational variety of English that has specific features which belong to the literary and elevated language of the past. Literary language has been assigned a special status since antiquity, and is still used nowadays by some speakers and writers in certain situations and contexts. It has been considered as sublime and distinctive from all other types of language; one which is deviant from ordinary use of language in that it breaks the common norms or standards of language. A basic characteristic of literary style is linguistic deviation which occurs at different levels; lexical, semantic, syntactic, phonological, morphological, graphological, historical, dialectal and register. All these types of deviations are thoroughly investigated and stylistically analyzed in this paper so as to acquaint readers, students of English, researchers, and those interested in the field, with this type of linguistic phenomenon whose data is based on selected samples from major classical works in English literatur

To What Extent Are Honeypots and Honeynets Autonomic Computing Systems?

Cyber threats, such as advanced persistent threats (APTs), ransomware, and zero-day exploits, are rapidly evolving and demand improved security measures. Honeypots and honeynets, as deceptive systems, offer valuable insights into attacker behavior, helping researchers and practitioners develop innovative defense strategies and enhance detection mechanisms. However, their deployment involves significant maintenance and overhead expenses. At the same time, the complexity of modern computing has prompted the rise of autonomic computing, aiming for systems that can operate without human intervention. Recent honeypot and honeynet research claims to incorporate autonomic computing principles, often using terms like adaptive, dynamic, intelligent, and learning. This study investigates such claims by measuring the extent to which autonomic principles principles are expressed in honeypot and honeynet literature. The findings reveal that autonomic computing keywords are present in the literature sample, suggesting an evolution from self-adaptation to autonomic computing implementations. Yet, despite these findings, the analysis also shows low frequencies of self-configuration, self-healing, and self-protection keywords. Interestingly, self-optimization appeared prominently in the literature. While this study presents a foundation for the convergence of autonomic computing and deceptive systems, future research could explore technical implementations in sample articles and test them for autonomic behavior. Additionally, investigations into the design and implementation of individual autonomic computing principles in honeypots and determining the necessary ratio of these principles for a system to exhibit autonomic behavior could provide valuable insights for both researchers and practitioners.Comment: 18 pages, 3 figures, 5 table

ZETA - Zero-Trust Authentication: Relying on Innate Human Ability, not Technology

Reliable authentication requires the devices and channels involved in the process to be trustworthy; otherwise authentication secrets can easily be compromised. Given the unceasing efforts of attackers worldwide such trustworthiness is increasingly not a given. A variety of technical solutions, such as utilising multiple devices/channels and verification protocols, has the potential to mitigate the threat of untrusted communications to a certain extent. Yet such technical solutions make two assumptions: (1) users have access to multiple devices and (2) attackers will not resort to hacking the human, using social engineering techniques. In this paper, we propose and explore the potential of using human-based computation instead of solely technical solutions to mitigate the threat of untrusted devices and channels. ZeTA (Zero Trust Authentication on untrusted channels) has the potential to allow people to authenticate despite compromised channels or communications and easily observed usage. Our contributions are threefold: (1) We propose the ZeTA protocol with a formal definition and security analysis that utilises semantics and human-based computation to ameliorate the problem of untrusted devices and channels. (2) We outline a security analysis to assess the envisaged performance of the proposed authentication protocol. (3) We report on a usability study that explores the viability of relying on human computation in this context

Constructive Ontology Engineering

The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in literature have been used in creating ontologies from various data sources such as structured data in databases or unstructured text found in text documents or HTML documents. Various data mining techniques, natural language processing methods, syntactical analysis, machine learning methods, and other techniques have been used in building ontologies with automated and semi-automated processes. Due to the vast amount of unstructured text and its continued proliferation, the problem of constructing ontologies from text has attracted considerable attention for research. However, the constructed ontologies may be noisy, with missing and incorrect knowledge. Thus ontology construction continues to be a challenging research problem. The goal of this research is to investigate a new method for guiding a process of extracting and assembling candidate terms into domain specific concepts and relationships. The process is part of an overall semi automated system for creating ontologies from unstructured text sources and is driven by the user’s goals in an incremental process. The system applies natural language processing techniques and uses a series of syntactical analysis tools for extracting grammatical relations from a list of text terms representing the parts of speech of a sentence. The extraction process focuses on evaluating the subject predicate-object sequences of the text for potential concept-relation-concept triples to be built into an ontology. Users can guide the system by selecting seedling concept-relation-concept triples to assist building concepts from the extracted domain specific terms. As a result, the ontology building process develops into an incremental one that allows the user to interact with the system, to guide the development of an ontology, and to tailor the ontology for the user’s application needs. The main contribution of this work is the implementation and evaluation of a new semi- automated methodology for constructing domain specific ontologies from unstructured text corpus