Vector Semantics Research Articles

Non-Classical Logics in Modern Science

Non-classical logicians have significantly expanded the traditional field of using logical methods. The first of them was the three-digit logic of Y. Lukasevich. Next came the three-digit logic of A. Bochvar, the "quantum logics" of G. Reichenbach and P. Detush-Fevrier, infinite-valued, probabilistic and other logics. The possibilities of non-classical logics have become widely used in various branches of scientific knowledge. Polysemantic, fuzzy, intuitionistic, modal, relevant and paranoherent, temporal and other non-classical logics are widely used today in physics, computational mathematics, computer science, linguistics, jurisprudence, ethics and other fields of natural science and socio-humanitarian knowledge. The recently increased interest in non-classical logics is explained, first of all, by the fact that various philosophical, syntactic, semantic and metalogical problems that were previously discussed in the scientific community are being replaced by practical interests. The main source of such interest is their wide application in computer science, artificial intelligence and programming. The logic of causality is used in the interpretation of the concepts of "law of nature", "ontological necessity" and "determinism"; temporal modal logics - for modeling, specification and verification of software systems of logical control; logics with vector semantics, combining the features of fuzzy and para-contradictory logics - in solving problems of dynamic verification of production knowledge bases and expert systems.

A Meaning Apart from Its Indistinguishable Words

ABSTRACT What difference did Hawthorne make in nineteenth-century US fiction? An unanswerable question, yet one that we can begin to address in a surprisingly literal way by using word embeddings to analyze the large corpora of nineteenth-century US fiction now available. To specify this question, how does a corpus of nineteenth-century US fiction including Hawthorne differ from one wherein his work is experimentally excluded? Using this approach, I show how Hawthorne’s work changed the vector semantics of US fiction. Readers of Hawthorne will be pleased if unsurprised to find his characteristic ambivalence reaffirmed by quantitative methods. More novel is the new evidence this method provides for measuring the ways in which Hawthorne distinctively differs from his peers. Because the model reveals which words Hawthorne embedded most similarly and most dissimilarly from his contemporaries, we can take these quantitative and qualitative differences in word usage as starting-points from which to address the question that began this abstract. The article concludes with a reading of Hawthorne’s distinctive use of the word “likewise,” focusing on how it advances the satire of “The Procession of Life.”

Drawing constitutional boundaries: A digital historical analysis of the writing process of Pinochet’s 1980 authoritarian constitution

Drawing conceptual boundaries is one of the defining features of constitution-making processes. These historically situated operations of boundary making are central to the definition of what counts as “constitutional” in a political community. In this article, we study the operations of conceptual delimitation performed by the Constitutional Commission (1973–1978) that drafted the 1980 Chilean Constitution, the trademark of Augusto Pinochet’s dictatorship. Using the eleven volumes of the Commission’s Official Records as our textual material (10,915 pages and 80,005 distinct words), we apply vector semantics, spectral clustering and bigram graph-based analysis to explore conceptual boundaries and the behavior of specific keywords shaping the space of constitutional meanings. Our results identify the ways in which the Commission defines the normative horizon of the new social and political order by transforming old semantic references into a renewed conceptual framework. This analysis shows the immanent relations between political action and conceptual elaboration that underlie the creation of constitutional texts, as well as the potential of computational methods for the study of constitutional history and constitution-making processes.

Linguistic changes in the transition from summaries to abstracts: The case of the Journal of Experimental Medicine

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Extracting video games rating labels from transcript files

Video games industry represents one of the most profitable activities connected with entertainment and visual arts. Video game industry involves a great number of different professionals who work together to create products expected to reach people in many countries. A substantial part of these people are teenagers, strongly attracted and influenced by video games. For these reasons, various systems of labels have been created. These systems are based on different criteria, but they have in common the presence of descriptors, or labels, whose indicate the type of contents in the game. These labels give an age range indicator to inform the buyers and users to the more suitable age for the product. One of these systems is called PEGI, and we will primarily take it in consideration for the purposes of our study. The rating procedure includes a large process of manual control of each submitted game. In order to help this large and demanding process, we propose a system of video games rating based on automatic classification of the products performed over the “transcript” or script, files that display the full transcription of dialogues in a video game. The proposed automatic classification algorithm is based on specialized dictionaries enriched with a vector semantics algorithm, and is able to provide an age rating and a genre classification of video games. It works in a more efficient way in games with a consistent amount of dialogues. The experimentation of the proposed algorithm is returning encouraging results.

Influence of anomalous truth values on logical inference in VTF-logics as a basis for verification of rule-based systems

The paper is devoted to the problem of expert systems knowledge bases verification. The methodological basis of verification is logics with vector semantics in the VTF-logics form. The knowledge model is a rule-based system. The issues of algorithmization of contradictions and other problems detection are considered in the paper. Algorithmization is based on the characteristic features of in VTF-logics inference. It is shown that in the formalism under consideration, the anomalous truth of a small premise generates the same conclusion (a large premise is considered strictly true). Anomalies such as falsity, uncertainty, and contradiction are considered. The problems of reducing the computational complexity of algorithms are considered.

Word Embeddings for Constructive Comments Classification

Word embeddings are so significant today that it is common to see their application in multiple natural language tasks. Indeed, word embeddings as the first layer of a deep learning model are widely adopted and they can also be found in multiple natural language tasks such as classification of texts and named entity recognition. The focus of this paper is the identification of constructive online comments through the use of dense vector semantics such as word embeddings. We specifically explore two approaches: learning distributed word representations and the use of a pre-trained word embedding model. We evaluate these word embedding methods on a recently created constructive comments corpus comprised of 12,000 annotated news comments, intended to improve the quality of online discussions. The obtained results show how the performance of complicated architectures like recurrent and convolutional neural networks can be matched by a language model based on learning embeddings.

Computational Analysis versus Human Intuition: A Critical Comparison of Vector Semantics with Manual Semantic Classification in the Context of Plains Cree

A persistent challenge in the creation of semantically classified dictionaries and lexical resources is the lengthy and expensive process of manual semantic classification, a hindrance which can make adequate semantic resources unattainable for under-resourced language communities. We explore here an alternative to manual classification using a vector semantic method, which, although not yet at the level of human sophistication, can provide usable first-pass semantic classifications in a fraction of the time. As a case example, we use a dictionary in Plains Cree (ISO: crk, Algonquian, Western Canada and United States)

Verification of knowledge models by means of logic with vector semantics

The paper highlights the method of verification and identification of contradictions in the production knowledge bases using one class of logic with vector semantics, namely VTF-logic. The general verification algorithm is described. It is noted that the use of such logics, while maintaining the need to iterate over the input facts, offers a procedure of direct inference and analysis of the inconsistency only in the case of conclusions-hypotheses, characterized by the value of truth named “complete contradiction”. Tracing back the appropriate chain will identify and resolve the cause of the conflict.

Комплексная верификация продукционных баз знаний с использованием VTF-логик

In this paper, we consider a complex procedure for verifying rule-based knowledge bases using logics with vector semantics in the form of VTF-logic with a special representation of facts and rules. The described technique allows solving verification tasks such as identifying unrelated facts, identifying incomplete rules, identifying logical circles, checking the correspondence between a set of hypotheses and a set of terminal facts, identifying contradictions, identifying silent rules, and identifying abnormal breaks in the inference chains. Rules in the knowledge base are arranged in a causal way. It means if the same fact is included in the right part of one rule and the left part of another, the first rule is always performed earlier. As a result, the verification procedure is linear in terms of the number of rules and exponential in terms of the number of starting facts. However, the amount of calculations can be significantly reduced by selecting groups of facts related to a particular hypothesis. The novelty of the study is the use of logics with vector semantics for rules verification. This retains the ability to inference in case of anomalous values of truth. This logic provides to use the inference engine for dynamic verification of knowledge. As a result, you do not need to include additional architectural elements into the system (for example, rule set dependency chart), create external verification programs, etc. In fact everything is provided by regular means of the expert system. Static verification is provided by a special representation of facts and rules.

Static and dynamic vector semantics for lambda calculus models of natural language

Vector models of language are based on the contextual aspects of language, the distributions of words and how they co-occur in text. Truth conditional models focus on the logical aspects of language, compositional properties of words and how they compose to form sentences. In the truth conditional approach, the denotation of a sentence determines its truth conditions, which can be taken to be a truth value, a set of possible worlds, a context change potential, or similar. In the vector models, the degree of co-occurrence of words in context determines how similar the meanings of words are. In this paper, we put these two models together and develop a vector semantics for language based on the simply typed lambda calculus models of natural language. We provide two types of vector semantics: a static one that uses techniques familiar from the truth conditional tradition and a dynamic one based on a form of dynamic interpretation inspired by Heim’s context change potentials. We show how the dynamic model can be applied to entailment between a corpus and a sentence and provide examples.

ЛОГИКИ С ВЕКТОРНОЙ СЕМАНТИКОЙ КАК СРЕДСТВО ВЕРИФИКАЦИИ БАЗ ЗНАНИЙ

The paper discusses the general issues of automated search of artifacts in rule-based knowledge bases (KB) based on logic with vector semantics in the VTF-logic variant. Cases of falsity of antecedent of rules at all admissible values of truth of input premises, existence of terms which are not used anywhere and generation of uncertain values of truth, emergence of contradictions are considered. Automation is considered as the organization of the direct attached logical inference opening artifacts of KB. The first two cases are identified by counting the number of each rule triggering and identifying terms that are not tied to the rules. The contradiction is revealed by the verification of the truth of the conclusions-hypotheses. The presence of a conclusion with truth (1; 1) (complete contradiction) signals a contradiction at one of the stages of reasoning, which is set by the back trace of the logical chain. A necessary stage of inference is to combine the evidence using 11-composition (the second form of disjunction). The paper also presents the principle of calculating the truth of the conclusion based on the truth of the premises, the strategy of combining evidence, numerical measures that can be used in the conclusion.

SYMBOLIC TRANSFORMATION OF THE WIDOW`S IMAGE IN BIBLICAL CULTURAL TRADITION: SEMANTICS, ANALOGIES, UNIVERSAL FEATURES

The purpose of the work is to analyze the specific features of a widow’s image and status on the Bible pages, to consider semantic contexts of an image, to follow the parallels between the images of an orphan and a widow, to conceive a loneliness phenomenon and orphans’ and widows’ protection in Biblical tradition. Axiological variety and poly vector spiritual and semantic representation of Biblical women’images are the main focuses of the issue. Methodologically the issue is based on the original source of the Bible. The work is based on methodical description of the women’images, who are selected from the Old and New Testament in order to highlight valued features of each image. Moreover, the methods of semantic analysis and hermeneutics are applied to consider semantic differences. The principles of comparative analysis are applied in order to reveal the traits of a widow’s image in the blocks of historical texts and compare Ukrainian context of widows’ existence with biblical one. Scientific novelty is in the poly semantic analysis of the women’Biblical context and widows’ images separation with further analysis of their fates, valued statuses, which allowed them to embody the problems of motherhood and marriage, future children birth and solitude, the problem of divine protection in different ways. The issue is devoted to the consideration of symbolic and axiological poly vector transformations of the mentioned problems. Conclusions. The social polarity and spiritual separation of a widow’s place and role in ancient tradition, and poly vector semantics of a widow’s Biblical context are conceived. The attention is drawn to the varied …

Computation, Semantics, and Meaning: Adding to an Argument by Michael Gavin

Michael Gavin has published an article in which he uses ambiguity as a theme for juxtaposing close reading, a standard procedure in literary criticism, with vector semantics, a newer technique in statistical semantics with a lineage that includes machine translation. I take that essay as a framework of adding computational semantics to the comparison, which also derives from machine translation. After recounting and adding to Gavin’s account of 18 lines from Paradise Lost I use computational semantics to examine Shakespeare “The expense of spirit”. Close reading deals in meaning, which is ontologically subjective (in Searle’s usage) while both vector semantics and computational semantics are ontologically objective (though not necessarily objectively true, a matter of epistemology).

Vector Semantics, William Empson, and the Study of Ambiguity

Vector Semantics, William Empson, and the Study of Ambiguity

High-dimensional vector semantics

In this paper we explore the “vector semantics” problem from the perspective of “almost orthogonal” property of high-dimensional random vectors. We show that this intriguing property can be used to “memorize” random vectors by simply adding them, and we provide an efficient probabilistic solution to the set membership problem. Also, we discuss several applications to word context vector embeddings, document sentences similarity, and spam filtering.

THE APPLICATION OF VECTOR FORMALISM IN LOGIC AND LOGICAL-MATHEMATICAL MODELING

The article presents an overview of research related to the application of vector formalism in logical investigations. Three directions of research in this area are discussed. The first area has to deal with the complication of formalism of classical mathematical logic. It is based on the vectorization of the categories of Truth and Falsehood. This line of research is represented by a vector logic of E. Mizrahi and matrix logic of A. Stern. The second one is the vectorization of logical semantics. This approach is represented by the logic of K.I. Bakhtiyarov, neutrosophy logic of F. Smarandache and in the logics with vector semantics. The third area is devoted to vectorization syllogistics of Aristotle. Here vector representation is used for partial visualization and automation of building syllogisms. All three areas are of practical importance and can be used for the solution of applied problems, in particular, in computer science and artificial intelligence.

Vectorization technology to improve interpreter performance

In the present computing landscape, interpreters are in use in a wide range of systems. Recent trends in consumer electronics have created a new category of portable, lightweight software applications. Typically, these applications have fast development cycles and short life spans. They run on a wide range of systems and are deployed in a target independent bytecode format over Internet and cellular networks. Their authors are untrusted third-party vendors, and they are executed in secure managed runtimes or virtual machines. Furthermore, due to security policies or development time constraints, these virtual machines often lack just-in-time compilers and rely on interpreted execution. At the other end of the spectrum, interpreters are also a reality in the field of high-performance computations because of the flexibility they provide. The main performance penalty in interpreters arises from instruction dispatch. Each bytecode requires a minimum number of machine instructions to be executed. In this work, we introduce a novel approach for interpreter optimization that reduces instruction dispatch thanks to vectorization technology. We extend the split compilation paradigm to interpreters, thus guaranteeing that our approach exhibits almost no overhead at runtime. We take advantage of the vast research in vectorization and its presence in modern compilers. Complex analyses are performed ahead of time, and their results are conveyed to the executable bytecode. At runtime, the interpreter retrieves this additional information to build the SIMD IR (intermediate representation) instructions that carry the vector semantics. The bytecode language remains unmodified, making this representation compatible with legacy interpreters and previously proposed JIT compilers. We show that this approach drastically reduces the number of instructions to interpret and decreases execution time of vectorizable applications. Moreover, we map SIMD IR instructions to hardware SIMD instructions when available, with a substantial additional improvement. Finally, we finely analyze the impact of our extension on the behavior of the caches and branch predictors.

Substantial and formal deductions in logics with vector semantics

The problem of logic deduction for one class of logics with a vector semantics is discussed. In the given logics the trustiness is represented by a vector with components ?Truth; Lie?, which do not depend on each other. The problem of organization of "substantial" and "formal" deductions is considered. In the first case the meaning of truth (semantics) of judgements is taken into account, whereas in the second case only the structure of judgements (syntax) is considered.

An Acceptance Vector Semantics for Path Programs

In this paper, we consider two formal semantics for path programs. The first is a version of the net semantics introduced in [8] and further described in [7], and the second is an extension of the vector semantics of [15]. The extension involves the idea of tagging vectors with sets of sets of action names as with acceptance sets [3, 5] or refusal sets [1, 6] as used in the semantics of certain process algebras. The net semantics of [8, 7] associates a path program with an isomorphism class of labelled, marked nets - two such nets being isomorphic if they have identical pictorial representations and consequently describe the same system. A behaviour of such a class is an isomorphism class of cycle-free labeled nets showing the (partial) order in which conditions have held and events have occurred. We review these basic ideas and then present a version of the [7] semantics. We next present an acceptance vector semantics for path programs. An acceptance vector consists of a collection of sequences, one for each component path, describing the sequence of actions associated with the path in question during some period of activity, together with a set of actions which are available to continue the behaviour represented by the collection. Finally, we show that the two semantics are related in the sense that every net based behaviour may be transformed into an accceptance vector.