Using natural language processing in order to create SQL queries

djahantighi, F. Siasar; Norouzifard, Mohammad; Davarpanah, Seyyed Hashem; Shenassa, M.H.

doi:10.1109/iccce.2008.4580674

Cited by 20 publications

(8 citation statements)

References 3 publications

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“…An example similar to the robots is the one in this article [96] where the authors used NLP to create SQL statements. With this, the authors sought to bring SQL to non-professional users, so that they could write a sentence in natural language that was transformed to the corresponding query in SQL by using an expert system made in Prolog that contains the experience in that domain.…”

Section: Related Work On Nlpmentioning

confidence: 99%

A Review of Artificial Intelligence in the Internet of Things

García¹,

Núñez‐Valdéz²,

García‐Díaz³

et al. 2019

IJIMAI

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To carry out this idea, he proposed to make a child's brain instead of trying to make an adult brain, and thus educate it to obtain the brain of an adult. In this way, he divides the problem into two parts: the 'child' program and the education process. He explains that we should not expect the first 'child' machine to come out on the first attempt and that we should teach it to see how its learning evolves. Thus, after several attempts, they would be getting better machines (or even worse), something that Turing compared with the process of evolution and that several researchers would later develop under the name of genetic algorithms [3].

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Section: Related Work On Nlpmentioning

confidence: 99%

A Review of Artificial Intelligence in the Internet of Things

García¹,

Núñez‐Valdéz²,

García‐Díaz³

et al. 2019

IJIMAI

View full text Add to dashboard Cite

show abstract

“…The other applications of NLP include generating SQL queries from plain text based on synonymous words, [17] the flight schedule query system, [18] improving communications in e-democracy, [19] intrusion detection, [20] text encryption, [21] ontology based natural language processing for in-store shopping, [22] and software requirements specification analysis [23] etc.…”

Section: Literature Reviewmentioning

confidence: 99%

Domain Independent Natural Language Processing -- A Case Study for Hospital Readmission with COPD

Agarwal

Behara

Mulpura

et al. 2014

2014 IEEE International Conference on Bioinformatics and Bioengineering

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Natural language processing is a field of computer science, which focuses on interactions between computers and human (natural) languages. The human languages are ambiguous unlike Computer languages, which make its analysis and processing difficult. Most of the data present these days is in unstructured form (such as: Accident reports, Patient discharge summary, Criminal records etc), which makes it hard for computers to understand for further use and analysis. This unstructured text needs to be converted into structured form by clearly defining the sentence boundaries, word boundaries and context dependent character boundaries for further analysis. This paper proposes a component-based domain-independent text analysis system for processing of the natural language known as Domain-independent Natural Language Processing System (DINLP). Further the paper discusses the system capability and its application in the area of bioinformatics through the case study

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“…A query can be entered in natural language by the user. When the user enters the query in English, it is then translated into an SQL query [5]. There are many difficulties in converting NLQs to SQL queries, such as complexity, which implies that a single term may have several meanings.…”

Section: Introductionmentioning

confidence: 99%

A Natural Language Interface to Relational Databases Using an Online Analytic Processing Hypercube

Hazboun

Owda

2021

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Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse objects. To obtain or manipulate the data from relational databases, the user must be familiar with SQL and must also write an appropriate and valid SQL statement. However, users who are not familiar with SQL are unable to obtain relevant data through relational databases. To address this, we propose a Natural Language Processing (NLP) model to convert an NLQ into an SQL query. This allows novice users to obtain the required data without having to know any complicated SQL details. The model is also capable of handling complex queries using the OLAP cube technique, which allows data to be pre-calculated and stored in a multi-dimensional and ready-to-use format. A multi-dimensional cube (hypercube) is used to connect with the NLP interface, thereby eliminating long-running data queries and enabling self-service business intelligence. The study demonstrated how the use of hypercube technology helps to increase the system response speed and the ability to process very complex query sentences. The system achieved impressive performance in terms of NLP and the accuracy of generating different query sentences. Using OLAP hypercube technology, the study achieved distinguished results compared to previous studies in terms of the speed of the response of the model to NLQ analysis, the generation of complex SQL statements, and the dynamic display of the results. As a plan for future work, it is recommended to use infinite-dimension (n-D) cubes instead of 4-D cubes to enable ingesting as much data as possible in a single object and to facilitate the execution of query statements that may be too complex in query interfaces running in a data warehouse. The study demonstrated how the use of hypercube technology helps to increase system response speed and process very complex query sentences.

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Using natural language processing in order to create SQL queries

Cited by 20 publications

References 3 publications

A Review of Artificial Intelligence in the Internet of Things

A Review of Artificial Intelligence in the Internet of Things

Domain Independent Natural Language Processing -- A Case Study for Hospital Readmission with COPD

A Natural Language Interface to Relational Databases Using an Online Analytic Processing Hypercube

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