scholarly journals APPLICABILITY OF THE THESAURUS APPROACH TO MODELLING THE LEXICALSEMANTIC STRUCTURE OF A TERMINOLOGICAL FIELD

2021 ◽  
Vol 23 (78) ◽  
pp. 13-16
Author(s):  
A.P. Zhuravlev ◽  
Keyword(s):  
Natural Language ◽  
Automatic Processing ◽  
Semantic Relations ◽  
Semantic Model ◽  
Lexical Semantic ◽  
Text Information ◽  
Subject Areas ◽  
Current Stage ◽  
The Way

This article is the first part of the research focused on the applicability of the thesaurus approach as one of the instruments for building a lexical-semantic model of terminological fields belonging to various subject areas. Among other issues the article points out that the way of researching linguistic facts has changed from their analysis and description to modelling. After reviewing a number of scientific works by various linguists, the author proves the applicability of the thesaurus approach to a corpus of scientific lexis for its proper description, particularly for revealing the most characteristic types of semantic relations for every given terminological field. The applicability of the thesaurus approach is also proved in terms of the current stage of IT development. From this prospective, the potential of the thesaurus approach is determined in terms of analysis and structuring large amounts of text information for further automatic processing. With all this being said, the author, however, draws the conclusion that the complete formalization of a natural language lexis is essentially impossible.

scholarly journals THESAURUS APPROACH AS THE INSTRUMENT FOR MODELLING LEXICAL-SEMANTIC STRUCTURE OF A TERMINOLOGICAL FIELD

2021 ◽  
Vol 23 (80) ◽  
pp. 18-22
Author(s):  
A.P. Zhuravlev ◽  
Keyword(s):  
Semantic Relations ◽  
Semantic Structure ◽  
Semantic Model ◽  
Lexical Semantic ◽  
Subject Areas ◽  
Basic Features

This article is the second part of the research focused on the applicability of the thesaurus approach as one of the instruments for building a lexical-semantic model of terminological fields belonging to various subject areas. Among other issues the author of the article analyses and compares a number of definitions of thesaurus found in scientific works provided by various linguists. On the basis of the analyses performed the author lays down some basic features of the thesaurus approach. Also, the issue of applicability of the thesaurus approach to lexical-semantic groups of various volume and formality degree is discussed. In addition to this, the author pays attention to analyses of some types of semantic relations between lexical units that form a terminological field.

Modelling of Semantic Processes and Evolutional Semantic Model

2019 ◽  
Vol 26 (27) ◽  
pp. 197-210 ◽  
Author(s):  
Anastasia Fedorova
Keyword(s):  
Key Words ◽  
Dynamic Models ◽  
Scientific Literature ◽  
Semantic Model ◽  
Vast Array ◽  
Special Procedure ◽  
Semantic Models ◽  
Semantic Evolution ◽  
Semantic Processes ◽  
The Way

In Linguistics the terms model and modelling have a vast array of meanings, which depends on the purpose and the object, and the type of the scientific research. The article is dedicated to the investigation of a special procedure of semantic processes modelling, deducing and substantiating the notion “evolutional semantic model”, the content and operational opportunities of which differ drastically from the essence and purpose of the known from the scientific literature phenomenon of the same name. In the proposed research this variety of modelling is oriented towards the description of the dynamics of the legal terms content loading, the estimation of possible vectors of the semantic evolution on the way of its terminalization/determinalization. The evolutional model of semantics has here as its basis the succession of sememes or series of sememes, the order of which is determined with accounting of a number of parameters. The typical schemes of the meaning development, illustrated by the succession of sememes, are considered to be the models of semantic laws (evolutional semantic models = EMS). Their function is the explanation of the mechanism and the order of the stages of the semantic evolution of the system of the words which sprung from one root on the way of its legal specialization, and, therefore, the proposed in the paper experience of semantic laws modelling differs from the expertise of the “catalogue of semantic derivations”, proposed by H. A. Zaliznjak, which doesn’t have as its purpose the explanation of meaning displacements, and from the notion of semantic derivation, models of derivation, dynamic models, worked out by O. V. Paducheva, which also only state such a displacement, without proving its reality. Key words: evolutional semantic model (EMS), modelling, semantic law, sememe, pre(law).

Fast Neural Network Engine for Natural Science Language Processing: A Drug-Search Case.

2020 ◽  
Author(s):  
Vadim V. Korolev ◽  
Artem Mitrofanov ◽  
Kirill Karpov ◽  
Valery Tkachenko
Keyword(s):  
Neural Network ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Natural Science ◽  
Therapeutic Agent ◽  
Semantic Relations ◽  
Chemical Data ◽  
Processing Methods ◽  
Modern Natural

The main advantage of modern natural language processing methods is a possibility to turn an amorphous human-readable task into a strict mathematic form. That allows to extract chemical data and insights from articles and to find new semantic relations. We propose a universal engine for processing chemical and biological texts. We successfully tested it on various use-cases and applied to a case of searching a therapeutic agent for a COVID-19 disease by analyzing PubMed archive.

PRINCIPAL PROBLEMS OF NATURAL LANGUAGE PROCESSING SYSTEMS

2018 ◽  
pp. 35-38
Author(s):  
O. Hyryn
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Syntactic Analysis ◽  
Syntactic Ambiguity ◽  
Grammatical Structure ◽  
English Sentence ◽  
Analysis Methods ◽  
The Way

The article deals with natural language processing, namely that of an English sentence. The article describes the problems, which might arise during the process and which are connected with graphic, semantic, and syntactic ambiguity. The article provides the description of how the problems had been solved before the automatic syntactic analysis was applied and the way, such analysis methods could be helpful in developing new analysis algorithms. The analysis focuses on the issues, blocking the basis for the natural language processing — parsing — the process of sentence analysis according to their structure, content and meaning, which aims to analyze the grammatical structure of the sentence, the division of sentences into constituent components and defining links between them.

To Predict or Not to Predict: Influences of Task and Strategy on the Processing of Semantic Relations

2007 ◽  
Vol 19 (8) ◽  
pp. 1259-1274 ◽  
Author(s):  
Dietmar Roehm ◽  
Ina Bornkessel-Schlesewsky ◽  
Frank Rösler ◽  
Matthias Schlesewsky
Keyword(s):  
Semantic Relatedness ◽  
Presentation Mode ◽  
Judgment Task ◽  
Sentence Context ◽  
Task Demands ◽  
Event Related Potential ◽  
Semantic Relations ◽  
Decision Task ◽  
Lexical Semantic ◽  
Experimental Environment

We report a series of event-related potential experiments designed to dissociate the functionally distinct processes involved in the comprehension of highly restricted lexical-semantic relations (antonyms). We sought to differentiate between influences of semantic relatedness (which are independent of the experimental setting) and processes related to predictability (which differ as a function of the experimental environment). To this end, we conducted three ERP studies contrasting the processing of antonym relations (black-white) with that of related (black-yellow) and unrelated (black-nice) word pairs. Whereas the lexical-semantic manipulation was kept constant across experiments, the experimental environment and the task demands varied: Experiment 1 presented the word pairs in a sentence context of the form The opposite of X is Y and used a sensicality judgment. Experiment 2 used a word pair presentation mode and a lexical decision task. Experiment 3 also examined word pairs, but with an antonymy judgment task. All three experiments revealed a graded N400 response (unrelated > related > antonyms), thus supporting the assumption that semantic associations are processed automatically. In addition, the experiments revealed that, in highly constrained task environments, the N400 gradation occurs simultaneously with a P300 effect for the antonym condition, thus leading to the superficial impression of an extremely “reduced” N400 for antonym pairs. Comparisons across experiments and participant groups revealed that the P300 effect is not only a function of stimulus constraints (i.e., sentence context) and experimental task, but that it is also crucially influenced by individual processing strategies used to achieve successful task performance.

MyrrorBot : A Digital Assistant Based on Holistic User Models for Personalized Access to Online Services

2021 ◽  
Vol 39 (4) ◽  
pp. 1-34
Author(s):  
Cataldo Musto ◽  
Fedelucio Narducci ◽  
Marco Polignano ◽  
Marco De Gemmis ◽  
Pasquale Lops ◽  
...  
Keyword(s):  
Natural Language ◽  
Information Needs ◽  
Effective Interaction ◽  
Personal Digital Assistant ◽  
User Profiling ◽  
Online Services ◽  
Intent Recognition ◽  
User Models ◽  
Time Required ◽  
The Way

In this article, we present MyrrorBot , a personal digital assistant implementing a natural language interface that allows the users to: (i) access online services, such as music, video, news, and food recommendation s, in a personalized way, by exploiting a strategy for implicit user modeling called holistic user profiling ; (ii) query their own user models, to inspect the features encoded in their profiles and to increase their awareness of the personalization process. Basically, the system allows the users to formulate natural language requests related to their information needs. Such needs are roughly classified in two groups: quantified self-related needs (e.g., Did I sleep enough? Am I extrovert? ) and personalized access to online services (e.g., Play a song I like ). The intent recognition strategy implemented in the platform automatically identifies the intent expressed by the user and forwards the request to specific services and modules that generate an appropriate answer that fulfills the query. In the experimental evaluation, we evaluated both qualitative (users’ acceptance of the system, usability) as well as quantitative (time required to complete basic tasks, effectiveness of the personalization strategy) aspects of the system, and the results showed that MyrrorBot can improve the way people access online services and applications. This leads to a more effective interaction and paves the way for further development of our system.

scholarly journals DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching

2019 ◽  
Vol 33 ◽  
pp. 7442-7449 ◽  
Author(s):  
Kun Zhang ◽  
Guangyi Lv ◽  
Linyuan Wang ◽  
Le Wu ◽  
Enhong Chen ◽  
...  
Keyword(s):  
Natural Language ◽  
Small Region ◽  
Psychological Research ◽  
Attention Mechanism ◽  
Semantic Relations ◽  
Semantic Matching ◽  
Close Attention ◽  
Original Sentence ◽  
Benchmark Datasets ◽  
Sentence Matching

Sentence semantic matching requires an agent to determine the semantic relation between two sentences, which is widely used in various natural language tasks such as Natural Language Inference (NLI) and Paraphrase Identification (PI). Among all matching methods, attention mechanism plays an important role in capturing the semantic relations and properly aligning the elements of two sentences. Previous methods utilized attention mechanism to select important parts of sentences at one time. However, the important parts of the sentence during semantic matching are dynamically changing with the degree of sentence understanding. Selecting the important parts at one time may be insufficient for semantic understanding. To this end, we propose a Dynamic Re-read Network (DRr-Net) approach for sentence semantic matching, which is able to pay close attention to a small region of sentences at each step and re-read the important words for better sentence semantic understanding. To be specific, we first employ Attention Stack-GRU (ASG) unit to model the original sentence repeatedly and preserve all the information from bottom-most word embedding input to up-most recurrent output. Second, we utilize Dynamic Re-read (DRr) unit to pay close attention to one important word at one time with the consideration of learned information and re-read the important words for better sentence semantic understanding. Extensive experiments on three sentence matching benchmark datasets demonstrate that DRr-Net has the ability to model sentence semantic more precisely and significantly improve the performance of sentence semantic matching. In addition, it is very interesting that some of finding in our experiments are consistent with the findings of psychological research.

scholarly journals Modalidades productivas artesanales: expresiones de “lo local” en un mundo globalizado?

2003 ◽  
Vol 3 ◽  
Author(s):  
Mónica B. Rotman
Keyword(s):  
Structural Adjustment ◽  
Structural Changes ◽  
The State ◽  
Cultural Phenomenon ◽  
Current Stage ◽  
The Way

Esbozamos en este trabajo algunas consideraciones respecto de las relaciones entre la globalización y el tema artesanal, así como analizamos de que manera se expresa en el universo de las artesanías la dicotomía globallocal. La etapa actual de globalización se ha traducido en nuestro país en procesos de ajuste estructural; éstos suponen la reducción de los ámbitos de incumbencia pública, la retracción del estado, políticas de privatizaciones y aperturas de fronteras. La pauperización del país afecta más fuertemente a los sectores productivos más débiles. La modalidad productiva de los artesanos y sus condiciones de inserción en el mercado los hace sumamente vulnerables a los cambios estructurales que se producen en la actualidad. La producción artesanal, frecuentemente considerada como una expresión privilegiada de ‘lo local’ constituye un interesante fenómeno económico-cultural desde donde pensar las cuestiones planteadas. Abstract This article offers some considerations regarding the relationships between the phenomena of globalization and craftsmanship, analyzing the way the latter universe expresses the global-local dichotomy. The current stage of globalization has been translated in Argentina in processes of structural adjustment, which implied the reduction of the environments of public incumbency, the retraction of the state, privatization policies, and so on. This pauperization of the country affects the productive sectors. The productive modality of the artisans and the specific conditions they participate in the market turn them extremely vulnerable to the structural changes that take place at the present time. The production of craftsmen, frequently considered a privileged expression of the “local””, constitutes an interesting economic-cultural phenomenon from where to think the outlined questions.

scholarly journals Learning Lexical Subspaces in a Distributional Vector Space

2020 ◽  
Vol 8 ◽  
pp. 311-329
Author(s):  
Kushal Arora ◽  
Aishik Chakraborty ◽  
Jackie C. K. Cheung
Keyword(s):  
Vector Space ◽  
Semantic Relations ◽  
Distributional Semantics ◽  
Word Embeddings ◽  
Word Similarity ◽  
Lexical Semantic ◽  
Novel Approach ◽  
Classification Tasks

In this paper, we propose LexSub, a novel approach towards unifying lexical and distributional semantics. We inject knowledge about lexical-semantic relations into distributional word embeddings by defining subspaces of the distributional vector space in which a lexical relation should hold. Our framework can handle symmetric attract and repel relations (e.g., synonymy and antonymy, respectively), as well as asymmetric relations (e.g., hypernymy and meronomy). In a suite of intrinsic benchmarks, we show that our model outperforms previous approaches on relatedness tasks and on hypernymy classification and detection, while being competitive on word similarity tasks. It also outperforms previous systems on extrinsic classification tasks that benefit from exploiting lexical relational cues. We perform a series of analyses to understand the behaviors of our model. 1 Code available at https://github.com/aishikchakraborty/LexSub .

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