ENGLISH-JAPANESE MACHINE TRANSLATION: VERB-BASED NOUN CLASSIFICATION APPROACH

1996 ◽  
Vol 05 (04) ◽  
pp. 367-401
Author(s):  
CHAI KIAT YEO ◽  
WAI KONG LAM ◽  
ING YANN SOON

A new approach to machine translation, capable of resolving different meanings of a verb in sentences of varying context, is described. The design revolves around the Verb Usage Frame (VUF) and the Noun Classification Hierarchy (NCH). VUF contains different context items which embody the different semantic usages of a verb under different contexts. The meaning of the verb is resolved through the classifications of its subject and object, achieved through the NCH. NCH returns not just the basic classification of a noun but also its super-classification. This allows thorough semantic analysis of both the verb and the noun. The entire design is implemented using object-oriented techniques and a prototype English-Japanese machine translator is built to illustrate the merits of the design.

2021 ◽  
Vol 10 (34) ◽  
Author(s):  
A.N SAK ◽  
◽  
E.V BESSONOVA ◽  

When constructing machine translation systems, an important task is to represent data using graphs, where words act as vertices, and relations between words in a sentence act as edges. One of these tasks at the first stage of the analysis is the classification of words as parts of speech, and at the next stage of the analysis to determine the belonging of words to the sentence members’ classes. The article discusses methods of parsing both on the basis of rules determined in advance by means of traditional object-oriented programming, and on the basis of analysis by means of graph convolutional neural networks with their subsequent training. Online dictionaries act as a thesaurus.


2017 ◽  
Vol 56 (05) ◽  
pp. 370-376 ◽  
Author(s):  
Roberto Pérez-Rodríguez ◽  
Luis E. Anido-Rifón ◽  
Marcos A. Mouriño-García

SummaryObjectives: The ability to efficiently review the existing literature is essential for the rapid progress of research. This paper describes a classifier of text documents, represented as vectors in spaces of Wikipedia concepts, and analyses its suitability for classification of Spanish biomedical documents when only English documents are available for training. We propose the cross-language concept matching (CLCM) technique, which relies on Wikipedia interlanguage links to convert concept vectors from the Spanish to the English space.Methods: The performance of the classifier is compared to several baselines: a classifier based on machine translation, a classifier that represents documents after performing Explicit Semantic Analysis (ESA), and a classifier that uses a domain-specific semantic an- notator (MetaMap). The corpus used for the experiments (Cross-Language UVigoMED) was purpose-built for this study, and it is composed of 12,832 English and 2,184 Spanish MEDLINE abstracts.Results: The performance of our approach is superior to any other state-of-the art classifier in the benchmark, with performance increases up to: 124% over classical machine translation, 332% over MetaMap, and 60 times over the classifier based on ESA. The results have statistical significance, showing p-values < 0.0001.Conclusion: Using knowledge mined from Wikipedia to represent documents as vectors in a space of Wikipedia concepts and translating vectors between language-specific concept spaces, a cross-language classifier can be built, and it performs better than several state-of-the-art classifiers.


2021 ◽  
Vol 49 (1) ◽  
pp. 206-213
Author(s):  
Augustyn Lorenc ◽  
Małgorzata Kuźnar ◽  
Tone Lerher

Proper planning of a warehouse layout and the product allocation in it, constitute major challenges for companies. In the paper, the new approach for the classification of the problem is presented. Authors used real picking data from the Warehouse Management System (WMS) from peak season from September to January. Artificial Neural Network (ANN) and automatic clustering by using Calinski-Harabasz criterion were used to develop a new classification approach. Based on the picking list the clients' orders were prepared and analyzed. These orders were used as input data to ANN and clustering. In this paper, three variants were analyzed: the reference representing the current state, variant with product relocation by using ANN, and the variant with relocation by using automatic clustering. In the research over 380000 picks for almost 1600 locations were used. In the paper, the architecture of the system module for solving the PAP problem is presented. Presented research proved that using multi-criterion clustering can increase the efficiency of the order picking process.


Author(s):  
Milan Mirkovic

The aim of the paper is to improve availability classifications of components for application in construction systems. Construction production systems belong to project-based systems with serial-parallel structures with or without redundant components, and the availability function has a significant impact on the performance indicators of components and systems. The main indicators of function of the components are the availability, capacity, costs, and project time. A new approach to classification makes it possible to choose the most appropriate methodology for assessing component availability in the bidding phase, and managing company?s machine park. The new classification approach was tested on a practical example. The results obtained confirmed the justification for extending the classical approach to the classification of the availability of components.


Author(s):  
Oleksandr Ostrohliad

Purpose. The aim of the work is to consider the novelties of the legislative work, which provide for the concept and classification of criminal offenses in accordance with the current edition of the Criminal Code of Ukraine and the draft of the new Code developed by the working group and put up for public discussion. Point out the gaps in the current legislation and the need to revise individual rules of the project in this aspect. The methodology. The methodology includes a comprehensive analysis and generalization of the available scientific and theoretical material and the formulation of appropriate conclusions and recommendations. During the research, the following methods of scientific knowledge were used: terminological, logical-semantic, system-structural, logical-normative, comparative-historical. Results In the course of the study, it was determined that despite the fact that the amendments to the Criminal Code of Ukraine came into force in July of this year, their perfection, in terms of legal technology, raises many objections. On the basis of a comparative study, it was determined that the Draft Criminal Code of Ukraine needs further revision taking into account the opinions of experts in the process of public discussion. Originality. In the course of the study, it was established that the classification of criminal offenses proposed in the new edition of the Criminal Code of Ukraine does not stand up to criticism, since other elements of the classification appear in subsequent articles, which are not covered by the existing one. The draft Code, using a qualitatively new approach to this issue, retains the elements of the previous classification and has no practical significance in law enforcement. Practical significance. The results of the study can be used in law-making activities to improve the norms of the current Criminal Code, to classify criminal offenses, as well as to further improve the draft Criminal Code of Ukraine.


2021 ◽  
Vol 11 (4) ◽  
pp. 1855
Author(s):  
Franco Guzzetti ◽  
Karen Lara Ngozi Anyabolu ◽  
Francesca Biolo ◽  
Lara D’Ambrosio

In the construction field, the Building Information Modeling (BIM) methodology is becoming increasingly predominant and the standardization of its use is now an essential operation. This method has become widespread in recent years, thanks to the advantages provided in the framework of project management and interoperability. Hoping for its complete dissemination, it is unthinkable to use it only for new construction interventions. Many are experiencing what happens with the so-called Heritage Building Information Modeling (HBIM); that is, how BIM interfaces with Architectural Heritage or simply with historical buildings. This article aims to deal with the principles and working methodologies behind BIM/HBIM and modeling. The aim is to outline the themes on which to base a new approach to the instrument. In this way, it can be adapted to the needs and characteristics of each type of building. Going into the detail of standards, the text also contains a first study regarding the classification of moldable elements. This proposal is based on current regulations and it can provide flexible, expandable, and unambiguous language. Therefore, the content of the article focuses on a revision of the thinking underlying the process, also providing a more practical track on communication and interoperability.


2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Anis Zouaghi ◽  
Mounir Zrigui ◽  
Georges Antoniadis ◽  
Laroussi Merhbene

We propose a new approach for determining the adequate sense of Arabic words. For that, we propose an algorithm based on information retrieval measures to identify the context of use that is the closest to the sentence containing the word to be disambiguated. The contexts of use represent a set of sentences that indicates a particular sense of the ambiguous word. These contexts are generated using the words that define the senses of the ambiguous words, the exact string-matching algorithm, and the corpus. We use the measures employed in the domain of information retrieval, Harman, Croft, and Okapi combined to the Lesk algorithm, to assign the correct sense of those proposed.


Author(s):  
Xi Liu ◽  
Yongfeng Yin ◽  
Haifeng Li ◽  
Jiabin Chen ◽  
Chang Liu ◽  
...  

AbstractExisting software intelligent defect classification approaches do not consider radar characters and prior statistics information. Thus, when applying these appaoraches into radar software testing and validation, the precision rate and recall rate of defect classification are poor and have effect on the reuse effectiveness of software defects. To solve this problem, a new intelligent defect classification approach based on the latent Dirichlet allocation (LDA) topic model is proposed for radar software in this paper. The proposed approach includes the defect text segmentation algorithm based on the dictionary of radar domain, the modified LDA model combining radar software requirement, and the top acquisition and classification approach of radar software defect based on the modified LDA model. The proposed approach is applied on the typical radar software defects to validate the effectiveness and applicability. The application results illustrate that the prediction precison rate and recall rate of the poposed approach are improved up to 15 ~ 20% compared with the other defect classification approaches. Thus, the proposed approach can be applied in the segmentation and classification of radar software defects effectively to improve the identifying adequacy of the defects in radar software.


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