scholarly journals Structuring Natural Language to Query Language: A Review

2020 ◽  
Vol 10 (6) ◽  
pp. 6521-6525
Author(s):  
B. Nethravathi ◽  
G. Amitha ◽  
A. Saruka ◽  
T. P. Bharath ◽  
S. Suyagya
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Database Management ◽  
Query Language ◽  
Native Language ◽  
Database Management System ◽  
Novice User ◽  
Complex Queries ◽  
Sql Query

SQL (Structured Query Language) is a structured language for specialized purposes used to communicate with the data stored in a database management system. It uses dynamic and sophisticated query commands for processing and controlling data in a database, which can become an obstacle for users with no previous experience. In order to address this constraint, we have analyzed the existing models in Natural Language Processing, which convert a native-language query into an SQL query. Thus, any novice user can use the SQL program and eliminate the need to generate any complex queries. This work is a detailed survey of the existing literature.

scholarly journals How Do the Engineer Students Learn the SQL Language?

2014 ◽  
Vol 4 (1) ◽  
pp. 18
Author(s):  
Márta Erzsébet Czenky
Keyword(s):  
Database Management ◽  
Native Language ◽  
Database Management System ◽  
Tutoring System ◽  
Education Systems ◽  
Error Message ◽  
E Learning ◽  
Sql Language ◽  
Log File ◽  
Sql Query

In the teaching of database management the teaching of standardized SQL language cannot be avoided. Until the appearance of e-learning education systems we could only support the learning of SQL language with showing example queries. Using e-learning education systems in the education enables using tests, tutorials, teacher feedbacks which facilitate the learning of SQL language. But still these education tools can not ensure that students receive error message and assessment for correctness of the query edited in database management system in their native language after running the SQL query. In order to accomplish these two latter purposes we wrote a SQL tutoring system which was used from 2012�??s autumn by the students. In the paper we describe the problems of learning the SQL language, the supporting methods for learning before installation of the SQL tutoring system and with analysis of data of log file of the SQL tutoring system the manner of students�?? learning of SQL.

scholarly journals Natural Language to SQL query Generation

2021 ◽  
Vol 9 (VI) ◽  
pp. 5069-5072
Author(s):  
Kiran Raj R
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Regular Expression ◽  
Parts Of Speech ◽  
Query Generation ◽  
Sql Query ◽  
Speech Tagging ◽  
The Web

Today, everyone has a personal device to access the web. Every user tries to access the knowledge that they require through internet. Most of the knowledge is within the sort of a database. A user with limited knowledge of database will have difficulty in accessing the data in the database. Hence, there’s a requirement for a system that permits the users to access the knowledge within the database. The proposed method is to develop a system where the input be a natural language and receive an SQL query which is used to access the database and retrieve the information with ease. Tokenization, parts-of-speech tagging, lemmatization, parsing and mapping are the steps involved in the process. The project proposed would give a view of using of Natural Language Processing (NLP) and mapping the query in accordance with regular expression in English language to SQL.

scholarly journals Assessing multilingual multimodal image description: Studies of native speaker preferences and translator choices

2018 ◽  
Vol 24 (3) ◽  
pp. 393-413 ◽  
Author(s):  
STELLA FRANK ◽  
DESMOND ELLIOTT ◽  
LUCIA SPECIA
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Empirical Evidence ◽  
Language Processing ◽  
Native Speaker ◽  
Native Language ◽  
Target Language ◽  
Image Description ◽  
The Core ◽  
Future Work

AbstractTwo studies on multilingual multimodal image description provide empirical evidence towards two questions at the core of the task: (i) whether target language speakers prefer descriptions generated directly in their native language, as compared to descriptions translated from a different language; (ii) whether images improve human translation of descriptions. These results provide guidance for future work in multimodal natural language processing by first showing that on the whole, translations are not distinguished from native language descriptions, and second delineating and quantifying the information gained from the image during the human translation task.

SQL Query Algorithm Based on Restricted Chinese

2013 ◽  
Vol 765-767 ◽  
pp. 1684-1688
Author(s):  
Xiao Na Ma ◽  
Bo Wei Li ◽  
Lin Wang
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Formal Model ◽  
Sentence Type ◽  
Research Problem ◽  
Research Topic ◽  
Natural Language Query ◽  
Query Algorithm ◽  
Sql Query

In order to make the users who didnt study the computer-related major can find the useful information in their familiar manner, it becomes a hot research topic to search in an interactive way using Chinese natural language. But because the complexity of Chinese, how to build of a formal model of natural language is always a difficult research problem. In this paper, by analysis the query sentence type in SQL based on the special database, we bring forward the rules and the context irrespective grammars of the restrictive Chinese that resolves the difficult comprehension problem in natural language processing. And aiming at the comprehension processing, we give the detailed arithmetic describing that can translate a natural language query of the restrictive Chinese to SQL.

scholarly journals Natural Language SQL Query Processing using Fuzzy Matching and Elimination Technique

2019 ◽  
Vol 9 (2S) ◽  
pp. 222-228
Keyword(s):  
Natural Language ◽  
Latent Dirichlet Allocation ◽  
Query Language ◽  
Noise Removal ◽  
Research Area ◽  
End User ◽  
Complex Queries ◽  
Important Research Area ◽  
Sql Query ◽  
Common User

In Structured Query Language (SQL), complex queries are difficult to write or understand by a user, because every user is not familiar with SQL. A common user can able to retrieve the information from the query databases using natural language is considered as an important research area. To improve the communication between databases application and naive user, an enhanced application with intelligent interface are needed. A fuzzy system with matching and elimination technique is designed in this research study, where SQL queries are formed from the input given by the user through several steps like noise removal, lexicon normalization and query formation. Then, the system uses the Latent Dirichlet Allocation (LDA) to extract the keywords from the input query. Finally, matching and elimination techniques are used to find the data, which is related to the input query given by end-user. When compared with the existing SQL techniques, the proposed fuzzy method achieved 91% and 90.5% accuracy, 95% and 93% precision, and 0.10 and 0.12 error rate for both 28 and 50 queries.

scholarly journals Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre

2021 ◽  
Vol 8 ◽  
Author(s):  
Benjamin Hunter ◽  
Sara Reis ◽  
Des Campbell ◽  
Sheila Matharu ◽  
Prashanthi Ratnakumar ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Query Language ◽  
Lung Nodule ◽  
Service Evaluation ◽  
Support Vector ◽  
Lung Nodules ◽  
Cancer Centre ◽  
Structured Query Language

Importance: The stratification of indeterminate lung nodules is a growing problem, but the burden of lung nodules on healthcare services is not well-described. Manual service evaluation and research cohort curation can be time-consuming and potentially improved by automation.Objective: To automate lung nodule identification in a tertiary cancer centre.Methods: This retrospective cohort study used Electronic Healthcare Records to identify CT reports generated between 31st October 2011 and 24th July 2020. A structured query language/natural language processing tool was developed to classify reports according to lung nodule status. Performance was externally validated. Sentences were used to train machine-learning classifiers to predict concerning nodule features in 2,000 patients.Results: 14,586 patients with lung nodules were identified. The cancer types most commonly associated with lung nodules were lung (39%), neuro-endocrine (38%), skin (35%), colorectal (33%) and sarcoma (33%). Lung nodule patients had a greater proportion of metastatic diagnoses (45 vs. 23%, p < 0.001), a higher mean post-baseline scan number (6.56 vs. 1.93, p < 0.001), and a shorter mean scan interval (4.1 vs. 5.9 months, p < 0.001) than those without nodules. Inter-observer agreement for sentence classification was 0.94 internally and 0.98 externally. Sensitivity and specificity for nodule identification were 93 and 99% internally, and 100 and 100% at external validation, respectively. A linear-support vector machine model predicted concerning sentence features with 94% accuracy.Conclusion: We have developed and validated an accurate tool for automated lung nodule identification that is valuable for service evaluation and research data acquisition.

Sign in / Sign up

Export Citation Format

Share Document