Structuring Natural Language to Query Language: A Review

Nethravathi, B; Amitha, G.; Saruka, A.; Bharath, T. P.; Suyagya, S.

doi:10.48084/etasr.3873

Cited by 8 publications

(3 citation statements)

References 20 publications

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“…GIZA-PP [11] is a statistical MT toolkit that is used to train word classes using maximum-likelihood criteria. This generates a file in the /model directory [12]:…”

Section: Developing the Translation Modelmentioning

confidence: 99%

Word Sense Disambiguation applied to Assamese-Hindi Bilingual Statistical Machine Translation

Barman,

Sarmah,

Basimatary

et al. 2024

Eng. Technol. Appl. Sci. Res.

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Word Sense Disambiguation (WSD) is concerned with automatically assigning the appropriate sense to an ambiguous word. WSD is an important task and plays a crucial role in many Natural Language Processing (NLP) applications. A Statistical Machine Translation (SMT) system translates a source into a target language based on phrase-based statistical translation. MT plays a crucial role in a WSD system, as a source language word may be associated with multiple translations in the target language. This study aims to apply WSD to the input of the MT system to enhance the disambiguation output. Hindi WordNet was used by selecting the most frequent synonym to obtain the most accurate translation. This study also compared Naïve Bayes (NB) and Decision Tree (DT) to test and build a WSD model. NB was more appropriate for the WSD task than DT when evaluated in the Weka machine learning toolkit. To the best of our knowledge, no such work has been carried out yet for the Assamese Indo-Aryan language. The applied WSD achieved better results than the baseline MT system without embedding the WSD module. The results were analyzed by linguist scholars. Furthermore, the Assamese-Hindi transliteration system was merged with the baseline MT system for the translation of proper nouns. This study marks a remarkable contribution to Assamese NLP, which is a low computationally aware Indian language.

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“…GIZA-PP [11] is a statistical MT toolkit that is used to train word classes using maximum-likelihood criteria. This generates a file in the /model directory [12]:…”

Section: Developing the Translation Modelmentioning

confidence: 99%

Word Sense Disambiguation applied to Assamese-Hindi Bilingual Statistical Machine Translation

Barman,

Sarmah,

Basimatary

et al. 2024

Eng. Technol. Appl. Sci. Res.

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“…The software makes use of effective methods like Data Structuring [25,26], Random File Access, and Dynamic Memory Allocations [27] for the purpose of automatically processing and representing the data and the results. The software was created with window-driven user interfaces in mind to make it easier to use [28].…”

Section: B Developing the Necessary Softwarementioning

confidence: 99%

An Efficient Methodology for Detecting the Vertical Movement of Structures

El-Ashmawy

2023

Eng. Technol. Appl. Sci. Res.

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Details regarding the public safety of engineering structures can be gleaned from measurements and monitoring. The development of a methodology for monitoring and analyzing structures' vertical displacement is explained in this paper. The developed methodology aims to add a new dimension to geometric leveling, and leveling routing, by applying a least squares solution for level network adjustment and performing statistical analysis to assess the change in vertical displacement. To monitor and analyze the vertical deformation of a building in Cairo, Egypt, the proposed methodology was utilized. Twenty monitoring points, five auxiliary points, and three local reference stations were utilized. All the measurements were taken with a geodetic invar staff and an automatic level with an attachment of a parallel plate micrometer. The observations were made for an interval of 81 months. The least squares adjustment technique was applied to obtain the adjusted levels and observations and to generate the required statistical data. The results of the subsequent epochs were compared to the results of the first epoch to determine the vertical movement of the monitoring points for each epoch. In addition, the significance of the present displacement was ascertained by comparing the values of vertical displacement to the determined 95% corresponding confidence intervals. The findings demonstrated that the building remained stable throughout the monitoring period. The case study demonstrates how effectively geometric leveling with least square adjustment can be used to monitor the vertical displacement of structures.

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“…The language used in the databases of this study is SQL (Structured Query Language) managed in distributed databases (data storage), which has as its main characteristic its ease of access to information and interpretation, without the need to have prior knowledge of Query code (Nethravathi, Amitha, Saruka & Bharath, 2020;Wang, Liu, He & Wang, 2018). This type of language is characteristic for the correct reading and interpretation of queries in databases and information systems.…”

Section: Model Proposal Structuring -Structured Query Languages -Sql ...mentioning

confidence: 99%

Sustainable manufacturing in the fourth industrial revolution: A big data application proposal in the textile industry

González

Hernández²,

Vásquez³

et al. 2022

JIEM

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Purpose: Design an industrial production model with a focus on industry 4.0 (Big Data) and decision-making analysis for small and medium-sized enterprises (SMEs) in the clothing sector that allows improving procedures, jobs and related costs within the study organization Develop a sustainable manufacturing proposal for the industrial textile sector with a focus on Big data (entry, transformation, data loading and analysis) in organizational decision making, in search of time and cost optimization and environmental impact mitigation related.Design/methodology/approach: The present research, of an applied nature, raises a value proposition focused on the planning, design and structuring of an industrial model focused on Big Data, specifically in the apparel manufacturing sector for decision-making in a structured and automated way with the methodological approach to follow: 1) Approach of production strategies oriented in Big Data for the textile sector; 2) Definition of the production model and configuration of the operational system; 3) Data science and industrial analysis, 4) Production model approach (Power BI) and 5) model validation. Methodological design of the investigation. 1) Presentation of the case study, where the current situational analysis of the company is carried out, formulation of the problem and proposal of solution for the set of data analyzed; 2) Presentation of a solution proposal focused on Big Data, on the identification of the industrial ecosystem and integration with the company's information systems, as well as the solution approach in the study and science of data in real time; 3) Presentation of the Model proposal for SQL structured databases in the loading, transformation and loading of important information for this study; 4) Information processing, in the edition of data in the M language of Power BI software, construction and elaboration of the model; 5) Presentation of the related databases, in the integration with the foreign key of the Master table and the transactional Tables; 6) Data analysis and presentation of the Dashboard, in the design, construction and analysis of the related study variables, as well as the approach of solution scenarios in the correct organizational decision makingFindings: The results obtained show an improvement in operational efficiency from the value-added proposal. Research limitations/implications: Currently, the number of studies applying Big Data technology for organizations in the textile and manufacturing sector in organizational decision making are limited. If analyzed from the local scene, there are few cases of Big Data implementation in the textile sector, as a consequence of the lack of projects and financing of value propositions. Another limiting factor in this research is the absence of digital information of high relevance for study and analysis, which leads to longer times in data entry and placement in information systems in real time. Finally, there is no data organizational culture, where there are processes and/or procedures for data registration and its transformation into clean data.Originality/value: This research integrates, as well as the correct organizational decision making For the verification of originality, the project search and systematic review of literature in the main online search engines are carried out for this research; In addition, the percentages of coincidence with online reviewers such as turnitin and plag.es are reviewed in the transparency of this study project.

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Structuring Natural Language to Query Language: A Review

Cited by 8 publications

References 20 publications

Word Sense Disambiguation applied to Assamese-Hindi Bilingual Statistical Machine Translation

Word Sense Disambiguation applied to Assamese-Hindi Bilingual Statistical Machine Translation

An Efficient Methodology for Detecting the Vertical Movement of Structures

Sustainable manufacturing in the fourth industrial revolution: A big data application proposal in the textile industry

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