scholarly journals Method of information obtaining from ontology on the basis of a natural language phrase analysis

2020 ◽  
pp. 322-330
Author(s):  
A.A. Litvin ◽  
◽  
V.Yu. Velychko ◽  
V.V. Kaverynskyi ◽  
◽  
...  
Keyword(s):  
Natural Language ◽  
A Priori ◽  
Sparql Query ◽  
Source Material ◽  
Natural Languages ◽  
Analysis Algorithm ◽  
Semantic Tree ◽  
Ontology Structure

A method for phrases analyzing in natural languages of inflective type (Ukrainian and Russian) has been developed. The method allows one to outline main expressed ideas and groups of words in the text by which they are stated. The semantic trees of propositions formed in this way, each of which expresses one specific idea, are a convenient source material for constructing queries to the ontology in the SPARQL language. The analysis algorithm is based on the following sequence of basic steps: word tokenize, determining of marker words and phrases, identifying available type of proposition, identifying nouns groups, building a syntactic graph of a sentence, building semantic trees of propositions based on existing types of propositions, substituting parameters from semantic trees of propositions in the corresponding SPARQL query templates. The choice of an appropriate template depends on the type of proposition expressed by a given semantic tree of a proposition. The sets of concepts received as an answer are tied as corresponding answers to the previously defined semantic tree of proposition. In case of non-receipt of information from the ontology, the reduction of noun groups is carried out to express more general concepts and the building queries using them. This allows us to get some answer, although not as accurate as when we use the full noun group. The use of SPARQL query templates requires an a priori known ontology structure, which is also proposed in this paper. Such a system is applicable for dialogue using chat-bots or for automatically receiving answers to questions from the text.

Contextualism and Semantic Minimalism

2015 ◽  
Author(s):  
Anne Bezuidenhout
Keyword(s):  
Natural Language ◽  
Philosophy Of Language ◽  
Recent Progress ◽  
A Priori ◽  
Context Sensitivity ◽  
Natural Languages ◽  
Compositional Model ◽  
Sentence Level ◽  
Semantic Minimalism ◽  
Mental Resources

The debate between contextualists and semantic minimalists about meaning/content is one that matters most to philosophers of language, even though the debate is not solely a philosophical one. There are at least three ways of casting the debate. Firstly, it can be cast as one about how and when semantic and pragmatic mental resources are used during ordinary conversational exchanges. This debate utilizes theories and methodologies from psychology. Secondly, it can be framed in terms of the logic of natural languages and how to incorporate context sensitivity into a formal, compositional model of natural-language sentence-level meaning. Thirdly, it can be approached from an analytic philosophy of language perspective, with the aim of clarifying various crucial concepts, such as the concepts of saying and implicating, using a priori methods. Ideally, these domains of research will produce outcomes that cohere with each other. This essay surveys recent progress in these three domains.

Linguistic Data Model for Natural Languages and Artificial Intelligence. Part 5. Introduction to Logic

Discourse ◽  
2020 ◽  
Vol 6 (3) ◽  
pp. 109-117
Author(s):  
O. M. Polyakov
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Logic ◽  
Natural Language ◽  
Semantic Interpretation ◽  
General View ◽  
World Model ◽  
Semantic Approach ◽  
Natural Languages ◽  
The World ◽  
Linguistic Aspect

Introduction. The article continues the series of publications on the linguistics of relations (hereinafter R–linguistics) and is devoted to an introduction to the logic of natural language in relation to the approach considered in the series. The problem of natural language logic still remains relevant, since this logic differs significantly from traditional mathematical logic. Moreover, with the appearance of artificial intelligence systems, the importance of this problem only increases. The article analyzes logical problems that prevent the application of classical logic methods to natural languages. This is possible because R-linguistics forms the semantics of a language in the form of world model structures in which language sentences are interpreted.Methodology and sources. The results obtained in the previous parts of the series are used as research tools. To develop the necessary mathematical representations in the field of logic and semantics, the formulated concept of the interpretation operator is used.Results and discussion. The problems that arise when studying the logic of natural language in the framework of R–linguistics are analyzed. These issues are discussed in three aspects: the logical aspect itself; the linguistic aspect; the aspect of correlation with reality. A very General approach to language semantics is considered and semantic axioms of the language are formulated. The problems of the language and its logic related to the most General view of semantics are shown.Conclusion. It is shown that the application of mathematical logic, regardless of its type, to the study of natural language logic faces significant problems. This is a consequence of the inconsistency of existing approaches with the world model. But it is the coherence with the world model that allows us to build a new logical approach. Matching with the model means a semantic approach to logic. Even the most General view of semantics allows to formulate important results about the properties of languages that lack meaning. The simplest examples of semantic interpretation of traditional logic demonstrate its semantic problems (primarily related to negation).

A UNIFIED AND SYNCHRONOUS GENERATING SYSTEM FOR MULTIPLE NATURAL LANGUAGES BASED ON CFG AND SEMANTIC LANGUAGE

2012 ◽  
Vol 10 (04) ◽  
pp. 1250033
Author(s):  
LI LI ◽  
HONGLAI LIU ◽  
QINGSHI GAO ◽  
PEIFENG WANG
Keyword(s):  
Natural Language ◽  
Natural Languages ◽  
Generating System

The sentences in several different natural languages can be produced congruously and synchronous by the new generating system USGS = {↔, GI|GI = (TI, N, B-RISU, C-treeI, S, PI, FI), I = 0, 1, 2, …, n}, based on Semantic Language(SL) theory, all are legitimate and reasonable, where, B-RISU is the set of basic-RISU, C-treeI is the set of category-trees, and FI is the set of functions in I-natural language. The characteristic of this new generating system is unified, synchronous and one by one corresponding, based on semantic unit theory and that the number of rules is several millions.

scholarly journals Natural Language Processing by Enhanced Honey Encryption Technique

2019 ◽  
Vol 8 (12S) ◽  
pp. 159-163
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Cyber Attacks ◽  
Binary Form ◽  
Brute Force ◽  
Natural Languages ◽  
Cipher Text ◽  
The Right ◽  
Binary Strings

Traditional encryption systems and techniques have always been vulnerable to brute force cyber-attacks. This is due to bytes encoding of characters utf8 also known as ASCII characters. Therefore, an opponent who intercepts a cipher text and attempts to decrypt the signal by applying brute force with a faulty pass key can detect some of the decrypted signals by employing a mixture of symbols that are not uniformly dispersed and contain no meaningful significance. Honey encoding technique is suggested to curb this classical authentication weakness by developing cipher-texts that provide correct and evenly dispersed but untrue plaintexts after decryption with a false key. This technique is only suitable for passkeys and PINs. Its adjustment in order to promote the encoding of the texts of natural languages such as electronic mails, records generated by man, still remained an open-end drawback. Prevailing proposed schemes to expand the encryption of natural language messages schedule exposes fragments of the plaintext embedded with coded data, thus they are more prone to cipher text attacks. In this paper, amending honey encoded system is proposed to promote natural language message encryption. The main aim was to create a framework that would encrypt a signal fully in binary form. As an end result, most binary strings semantically generate the right texts to trick an opponent who tries to decipher an error key in the cipher text. The security of the suggested system is assessed..

How to build a constructicon in five years

2021 ◽  
Vol 34 ◽  
Author(s):  
Laura A. Janda ◽  
Anna Endresen ◽  
Valentina Zhukova ◽  
Daria Mordashova ◽  
Ekaterina Rakhilina
Keyword(s):  
Open Access ◽  
Natural Language ◽  
Language Proficiency ◽  
Construction Grammar ◽  
Full Scale ◽  
Electronic Database ◽  
Natural Languages ◽  
Searchable Database ◽  
Qualitative Level ◽  
Syntactic Properties

Abstract We provide a practical step-by-step methodology of how to build a full-scale constructicon resource for a natural language, sharing our experience from the nearly completed project of the Russian Constructicon, an open-access searchable database of over 2,200 Russian constructions (https://site.uit.no/russian-constructicon/). The constructions are organized in families, clusters, and networks based on their semantic and syntactic properties, illustrated with corpus examples, and tagged for the CEFR level of language proficiency. The resource is designed for both researchers and L2 learners of Russian and offers the largest electronic database of constructions built for any language. We explain what makes the Russian Constructicon different from other constructicons, report on the major stages of our work, and share the methods used to systematically expand the inventory of constructions. Our objective is to encourage colleagues to build constructicon resources for additional natural languages, thus taking Construction Grammar to a new quantitative and qualitative level, facilitating cross-linguistic comparison.

Discovering Opinions from Customers' Unstructured Textual Reviews Written in Different Natural Languages

2014 ◽  
pp. 834-859
Author(s):  
Jan Žižka ◽  
František Dařena
Keyword(s):  
Decision Tree ◽  
Natural Language ◽  
Real World ◽  
Large Data ◽  
Main Question ◽  
Internet Shopping ◽  
Natural Languages ◽  
On Line ◽  
Multilingual Data ◽  
Textual Form

Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: “Are the customers satisfied? Can we improve our services?” One of possible feedbacks is allowing the customers to freely write their reviews using a simple textual form. The more reviews that are available, the better knowledge can be acquired and applied to improving the service. However, very large data generated by collecting the reviews has to be processed automatically as humans usually cannot manage it within an acceptable time. The main question is “Can a computer reveal an opinion core hidden in text reviews?” It is a challenging task because the text is written in a natural language. This chapter presents a method based on the automatic extraction of expressions that are significant for specifying a review attitude to a given topic. The significant expressions are composed using significant words revealed in the documents. The significant words are selected by a decision-tree generator based on the entropy minimization. Words included in branches represent kernels of the significant expressions. The full expressions are composed of the significant words and words surrounding them in the original documents. The results are here demonstrated using large real-world multilingual data representing customers' opinions concerning hotel accommodation booked on-line, and Internet shopping. Knowledge discovered in the reviews may subsequently serve for various marketing tasks.

Syntax

2018 ◽  
Author(s):  
Stephen Neale
Keyword(s):  
Twentieth Century ◽  
Natural Language ◽  
Logical Form ◽  
Natural Languages ◽  
Related Notion ◽  
Theories Of Mind ◽  
Contemporary Work ◽  
Linguistic Categories ◽  
Traditional Work ◽  
Syntactic Properties

Syntax (more loosely, ‘grammar’) is the study of the properties of expressions that distinguish them as members of different linguistic categories, and ‘well-formedness’, that is, the ways in which expressions belonging to these categories may be combined to form larger units. Typical syntactic categories include noun, verb and sentence. Syntactic properties have played an important role not only in the study of ‘natural’ languages (such as English or Urdu) but also in the study of logic and computation. For example, in symbolic logic, classes of well-formed formulas are specified without mentioning what formulas (or their parts) mean, or whether they are true or false; similarly, the operations of a computer can be fruitfully specified using only syntactic properties, a fact that has a bearing on the viability of computational theories of mind. The study of the syntax of natural language has taken on significance for philosophy in the twentieth century, partly because of the suspicion, voiced by Russell, Wittgenstein and the logical positivists, that philosophical problems often turned on misunderstandings of syntax (or the closely related notion of ‘logical form’). Moreover, an idea that has been fruitfully developed since the pioneering work of Frege is that a proper understanding of syntax offers an important basis for any understanding of semantics, since the meaning of a complex expression is compositional, that is, built up from the meanings of its parts as determined by syntax. In the mid-twentieth century, philosophical interest in the systematic study of the syntax of natural language was heightened by Noam Chomsky’s work on the nature of syntactic rules and on the innateness of mental structures specific to the acquisition (or growth) of grammatical knowledge. This work formalized traditional work on grammatical categories within an approach to the theory of computability, and also revived proposals of traditional philosophical rationalists that many twentieth-century empiricists had regarded as bankrupt. Chomskian theories of grammar have become the focus of most contemporary work on syntax.

SEMCL

2010 ◽  
Vol 1 (3) ◽  
pp. 1-19 ◽  
Author(s):  
Weisen Guo ◽  
Steven B. Kraines
Keyword(s):  
Semantic Web ◽  
Natural Language ◽  
Knowledge Sharing ◽  
Language Processing ◽  
Global Knowledge ◽  
Semantic Web Technologies ◽  
Natural Languages ◽  
Web Technologies ◽  
Language Knowledge ◽  
Cross Language

To promote global knowledge sharing, one should solve the problem that knowledge representation in diverse natural languages restricts knowledge sharing effectively. Traditional knowledge sharing models are based on natural language processing (NLP) technologies. The ambiguity of natural language is a problem for NLP; however, semantic web technologies can circumvent the problem by enabling human authors to specify meaning in a computer-interpretable form. In this paper, the authors propose a cross-language semantic model (SEMCL) for knowledge sharing, which uses semantic web technologies to provide a potential solution to the problem of ambiguity. Also, this model can match knowledge descriptions in diverse languages. First, the methods used to support searches at the semantic predicate level are given, and the authors present a cross-language approach. Finally, an implementation of the model for the general engineering domain is discussed, and a scenario describing how the model implementation handles semantic cross-language knowledge sharing is given.

A novel method for providing relational databases with rich semantics and natural language processing

2017 ◽  
Vol 30 (3) ◽  
pp. 503-525
Author(s):  
Kamal Hamaz ◽  
Fouzia Benchikha
Keyword(s):  
Natural Language ◽  
Data Storage ◽  
Language Processing ◽  
Relational Database ◽  
Relational Databases ◽  
Data Access ◽  
New Techniques ◽  
Content Type ◽  
Semantic Tree ◽  
Novel Method

Purpose With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources. Design/methodology/approach First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree. Findings The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query. Originality/value Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.

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