Системный анализ задачи моделирования естественного языкa

The aim of this paper is to investigate the usage of articles (i.e., definiteness and specificity) in natural (i.e., English, Samoan, and Lillooet Salish) and artificial (i.e., Esperanto, Unish, and Sambahsa) languages and then to suggest an optimal pattern of articles in artificial languages. The observation in this paper is supported by the typology of articles in natural languages, language acquisition, markedness of articles, and historical developments of articles. Then, it proposes that articles are a recent and uncommon grammatical realization and show great variation across languages. Finally, this paper proposes the ‘Minimal Realization Principle’ for article uses in artificial languages.

An universal method for wordform recognition and generation is proposed. It includes the model of word formation in natural languages and algorithms for wordform generation and recognition. In the wordformation model, abstracting from typical notions in the morphology of natural languages takes place Actual problems of machine translation, spelling checking, text analysis and knowledge extraction from them, computer–user dialog in a natural language, analysis of queries in information search systems of global information networks include multilevel automatic text processing. This levels are morphological, syntax and semantic. There are a large number of methods for solving the morphological level problems in text processing (see short review in [1]). However, they are designed for one or several languages that are similar in their word formation. At the same time, in connection with worldwide globalization, it is topical to develop applications for text pro cessing in different languages. Therefore, the necessity arises to create a method for morphological processing of texts in natural languages of different groups and families. This work proposes a universal method for the generation and recognition of word forms independent of the formation type and capable of processing the entire paradigm of a word. The method includes a model for the formation and wordform generation and recognition algorithm. The Model of formation in a natural language (below the model of formation) implies that the generation of any word form with a given grammatical meaning can be presented as the sequence of a finite number of transformations of the base. The method of presenting formation, as well the generation and recognition algorithms are interrlated. On the one hand, one part governs the other. On the other, simplification of one part causes complication of the other. The objective of the word form generation algorithm is to obtainthe word form F corresponding to the base S and grammatical meaning G. The result of word form generation is always unambiguous. The input data are S and G. The output data are F. The generation algorithm consists of two stages. At the first stage a required transformation chain R is searched using the input data, the base S, and grammatical meaning G. The second stage is the application of the found chain R to the base S to obtain the required form F. The wordform recognition algorithm recognizes the grammatical meaning G and the base S that correspond to the starting word form F. The input data are F. The output data are S and G. This algorithm consists in searching the chains of transformations in a cycle. At each iteration, a new chain Ri is taken as well as a respective base type Ti and a grammatical meaning Gi. Further, the next reverse chain is applied to the starting word form F to obtain the base Si. If the same base type Ti corresponds to the found base Si and the next chain then the result that consists of the obtained chain Si and the grammatical meaning Giis added to the obtained results. Thus, the iteration is completed and a transition to the next iteration occurs. The number of iterations equals n, the number of the chains of transformations. Thus, we have developed a universal method for wordform generation and recognition that includes the model of formation and the processing algorithm. The proposed processing algorithms are applicable to natural languages of different groups and families. Algorithms for the Russian, German, Spanish, and Finnish languages were successfully tested. The transformation chains were classified and the algorithm of automated construction of transformation chains was proposed based on this classification.

The research aims are to find out the concept of semantics constructed in the “ Massure” poetry and to find out the meaning of “Massure” poetry by Muskamal Bare in city of Bone, South Sulawesi. In this study, the writer used descriptive qualitative method to analyzed data. The writer observed the location, interviewed to the author and some people in Bone, South Sulawesi , and used some tools as documentation which relate to the research in Bone, South Sulawesi.“Massure“ poetry has a lexical meaning and grammatical meaning. Lexical meaning that is the meaning of each word and grammatical meaning that is the meaning of each sentence. So there are differences among lexical and grammatical meaning that contained in “ Massure” poetry by Muskamal Bare in Bone , South Sulawesi.“ Massure “ is the delivery or coveying a story Either it is about the kingdom ,hero, natural disasters and etc. In this poetry talking about customs in the kingdom of Bone. Anyone who violates customs as good as he makes all people angry and been a disaster by many people.

: This research focuses on the lexical and grammatical meanings in the lyrics of Keisya Levronka's song "Tak Lagi Usai". This study uses a semantic approach. The purpose of this study is to first explain the grammatical meaning in the lyrics of the song "Tak Lagi Usai" by Keisya Levronka. The second explains the lexical meaning in the lyrics of Keisya Levronka's song "Unwanted to End". The research method used is descriptive qualitative method. This research is descriptive qualitative which means using interpretation (interpretative). The source of the data used is the song "Unwanted to End" by Keisya Levronka. The data analysis technique used is note-taking, namely by analyzing the grammatical and lexical meanings contained in the lyrics of the song "Tak Lagi Usai" by Keisya Levronka. The data in this study are all words, phrases, clauses, and sentences contained in the lyrics of Keisya Levronka's song "Tak Lagi Usai" which contain grammatical and lexical meanings. The results of the research conducted by the researcher concluded that there were 40 data, namely the first data of grammatical meaning, there were 22 data. Then the second data about lexical meaning there are 18 data.

This chapter examines possibilities for pragmemes and practs in artificial languages, and whether and how artificial languages differ in these respects from natural languages. In some controlled languages (a type of artificial language), it is only possible to discuss a small set of topics, meaning that the set of possible pragmemes is small. Some other artificial languages are designed for use by a particular group of people, in some cases by only one person. Such differences seem to make some artificial languages quite unlike natural languages; that is, although artificial languages, no matter how strange they may seem on the surface, seem to resemble natural languages in some areas (e.g. syntax), with respect to pragmemics they appear very different. However, if artificial languages are used to report on pragmemes (e.g. in fiction), they may (and may have to) allow for a wider range of pragmemes and practs.

This thesis is concerned with the analysis and generation of pictures by computer. The name "picture processing" will be used to describe this subject area. While there is occasional reference to generation, the main emphasis is on the more difficult problem of analysis. The latter has been traditionally called pattern recognition or classification; here, analysis is interpreted more generally to mean the derivation of. picture descriptions. A distinction between "natural" and "artificial" pictures can be I made analogous to that between natural and artificial languages. Artificial languages and subsets of natural languages can be effectively analyzed using formal methods for expressing and dealing with syntax and semantics. A similar approach has been developed here for the analysis of suitably restricted classes of pictures. Any picture whose component connectivity can be meaningfully described by a graph is a candidate for the system. This will be the operational definition of an artificial picture.

This research discusses a semantic study of the poem "Sia-Sia," which is part of "Aku Ini Binatang Jalang" by Chairil Anwar, focusing on lexical and grammatical meaning. The purpose of this study is to describe and analyze the forms of lexical and grammatical meanings contained within the poem. This research employs a qualitative descriptive method, with data collection conducted through literature study, observation, and note-taking. Data analysis follows the Miles and Huberman model, consisting of three stages: data reduction, data presentation, and conclusion drawing.Based on the analysis of the poem, the researcher identified various forms of both lexical and grammatical meanings—four meanings that align with their original intent and three meanings influenced by contextual factors within the sentence. The results show that Chairil Anwar’s poetry not only possesses high aesthetic value but is also rich in semantic meaning. Thus, this study demonstrates that a semantic analysis of "Aku Ini Binatang Jalang" enhances readers’ understanding of the depth of meaning contained in each line of the poem, while affirming the linguistic richness and expressive power of Chairil Anwar as a great poet in Indonesian literature. ABSTRAKPenelitian ini membahas kajian semantik terhadap sajak sia-sia bagian dari Aku Ini Binatang Jalang karya Chairil Anwar dengan fokus pada mengkajian pemaknaan leksikal dan gramatikal. Tujuan penelitian ini adalah untuk mendeskripsikan menganalisis bentuk-bentuk makna leksikal dan gramatikal yang termuat dalam puisi tersebut. Penelitian ini menggunakan metode deskriptif kualitatif dengan teknik pengumpulan data melalui studi pustaka, observasi, dan pencatatan. Analisis data dilakukan dengan model Miles dan Huberman melalui tiga tahap, yaitu reduksi data, penyajian data, dan penarikan kesimpulan. Berdasarkan sajak yang dikaji, peneliti menemukan bentuk makna yang beragam leksikal maupun gramatikal, yaitu 4 sesuai dengan maksud aslinya dan 3 makna yang dapat terpengaruh oleh konteks kalimatnya. Hasil penelitian menunjukkan bahwa puisi karyanya ini tidak hanya memiliki nilai estetika yang tinggi, tetapi juga kaya akan makna semantik. Dengan demikian, kajian ini menunjukkan bahwa analisis semantik terhadap puisi Aku Ini Binatang Jalang memperkuat pemahaman pembaca terhadap kedalaman makna yang terkandung dalam setiap larik puisi, sekaligus menegaskan kekayaan bahasa dan kekuatan ekspresi Chairil Anwar sebagai penyair besar dalam sastra Indonesia.

A top-down language analyzer

The article examines the problem of the dialectic nature of the language system. The analysis of a number of works on the philosophy of language has shaped research logic of authors, which guided the definition of the concepts of “natural language” and “artificial language”. It is shown that the “natural – artificial” dichotomy in a language system is revealed through the prism of a number of paired constructs: “natural – social”, “oral – written”; “folk – literary”; “informal – etiquette-formal”; “objective – subjective”; “autochthonous – borrowed”; “traditional – innovative”. The different genesis of the natural and artificial languages proves that the artificial languages are aimed at the intended result, while the natural can be considered as a side effect of communicative-linguistic activity, which is not provided by its purposes.

This paper discusses a variety of questions regarding the form and function of relative pronouns in artificial languages. In the first major part of the paper information about relative pronouns in natural languages is presented. From this part the prospective language designer will get an idea of the range of relevant possibilities occurring in natural languages. The second major part shows some of the choices which languages designers have made with respect to relative pronouns in their languages. Generally these choices have been within a narrow range， that is， not all of the possibilities of natural languages have been selected for artificial languages. Specifically，the morphology and syntax of relative pronouns quite often resembles that of Indo-European languages， which is not surprising， since most language designers have been native speakers of an lndo­European language， and many artificial languages have been based on one or more of these languages. The final section of the paper contains some recommendations for the design and use of relative pronouns in artificial languages.

The processing of information for supporting human knowledge based processes still represents a big challenge. This is caused both by the abstract concept of the information and by missing a suitable information representation (how to represent human knowledge), which would enable a human—computer communication in natural language. However, any interdisciplinary definition of “information” or even “knowledge” does not exist until now. In the period 2010 to 2012, the authors presented their research approach to the automation of teaching processes as typical human knowledge based processes within the WCE’s International Conference on Education and Information Technology. The following research showed that solving the automation of the knowledge processes requires one to solve not only a content knowledge processing but also issues of communication, transmission and feedback. Actually, the research covers some areas of computer science (e.g. computer applications, computing methodologies, theoretical computer science). The question of the information was solved by the design of a specific default data structure so called virtual knowledge which enables an individual to communicate with computer in natural language. In this context, the virtual knowledge unit symbolizes an information representation for human knowledge which is readable both by a human and machine. Such approach enables one to input any kind of information from human resources into the virtual knowledge and to process human knowledge as it is typical for computers. This contribution illustrates how various kind of information from human sources are processed by the in-house software BIKE. It also enables one to understand why the software works as an all-in-one tool when processing human knowledge which is inputted into the virtual knowledge. In addition, the information transmission in the knowledge based processes was solved by a specific utility model for processing unstructured data.

With the advent of the computer era, artificial languages had to be conceived in order to communicate with machines. To exchange this inconvenient means with everyday spoken human utterances, a more intense look at Natural Languages and their formalizations has become necessary. Only a profound understanding of Natural Language fundamentals provides conditions under which the architecture of computer hardware can be developed and adapted to future linguistic requirements. The meaning of the terms “formalization” and “Natural Language” is defined in Sections 1.3 and 1.4. These two preliminary sections also emphasize the importance of recognizing Natural Language phenomena for optimization and rationalization of machineless man-man communication. The requirement of a new and comprehensive approach to formalize Natural Languages by emphasizing isolated instead of agglutinated morphologies is indicated in the last two sections of this introduction.KeywordsNatural LanguageTraffic SignArtificial LanguageSpeech Recognition SystemAutomatic Speech Recognition SystemThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The problem of analytical means used for word formation and for the realization of grammatical meaning has repeatedly been the subject of study in the works of European Turkologists and Turkish linguists. However, the analysis of the relevant literature and the proposed solutions have led to the conclusion that there are many differences between the concepts and hypotheses of various authors: from a narrow understanding of analytics at the lexical and grammatical levels to a maximally broad one, where forms and formations that, in our opinion, do not correspond at all to the definition of an analytical means are improperly included in this class of means. In this work, we examine the concepts of various linguists both classical and modern, who published their works within the last decade, as they are of greatest interest because they demonstrate no significant progress in the positions and views on the problem of analytics in the system of the Turkish language over the past fifty years. The article investigates diverse lexical and grammatical forms that meet the main requirement for analytical means, which comes down to the presence of a full-fledged element containing the main lexical meaning, and an auxiliary verb that has no autonomous lexical meaning but creates a new lexeme (the so-called “compound verb”) or modifies the lexical meaning for a grammatical purpose (primarily in terms of realizing internal tense or modal meanings). The article describes the concepts regarding the genesis of analytical forms in Turkish and the Turkic languages and proposes a group classification of analytical grammatical means: periphrastic verb forms, compound verb forms, quasi-periphrastic verb forms, set verbal formations, and set phrases, which are formally correlated with analytical forms but significantly differ from them from the semantic and functional points of view. The paper concludes by outlining prospects for further research into set verbal collocations in Turkish.

The operational complexity and dynamicity of clouds highlight the importance of automated solutions for explaining the root cause of security incidents. Most existing works rely on human analysts to interpret provenance graphs for root causes of security incidents. However, navigating and understanding a large and complex cloud-scale provenance graph can be very challenging for human analysts. Without such an understanding, cloud providers cannot effectively address the underlying security issues causing the incidents, such as vulnerabilities or misconfigurations. In this paper, we propose VinciDecoder, an automated approach for generating natural language forensic reports based on provenance graphs. Our main observation is that the way nodes and edges compose a path in provenance graphs is similar to how words compose a sentence in natural languages. Therefore, VinciDecoder leverages a novel combination of provenance analysis, natural language translation, and machine-learning techniques to generate forensic reports. We implement VinciDecoder on an OpenStack cloud testbed, and evaluate its performance based on real-world attacks. Our user study and experimental results demonstrate the effectiveness of our approach in generating high-quality reports (e.g., up to 0.68 BLEU score for precision).

Because of the hierarchical organization of natural languages, words that are syntactically related are not always linearly adjacent. For example, the subject and verb in the child always runs agree in person and number, although they are not adjacent in the sequences of words. Since such dependencies are indicative of abstract linguist structure, it is of significant theoretical interest how these relationships are acquired by language learners. Most experiments that investigate nonadjacent dependency (NAD) learning have used artificial languages in which the to-be-learned dependencies are isolated, by presenting the minimal sequences that contain the dependent elements. However, dependencies in natural language are not typically isolated in this way. We report the first demonstration to our knowledge of successful learning of embedded NADs, in which silences do not mark dependency boundaries. Subjects heard passages of English with a predictable structure, interspersed with passages of the artificial language. The English sentences were designed to induce boundaries in the artificial languages. In Experiment 1 & 3 the artificial NADs were contained within the induced boundaries and subjects learned them, whereas in Experiment 2 & 4, the NADs crossed the induced boundaries and subjects did not learn them. We take this as evidence that sentential structure was "carried over" from the English sentences and used to organize the artificial language. This approach provides several new insights into the basic mechanisms of NAD learning in particular and statistical learning in general. (PsycINFO Database Record