A Novel Approach Towards Building a Portable NLIDB System Using the Computational Paninian Grammar Framework

Gupta, Abhijeet; Akula, Arjun R.; Malladi, Deepak; Kukkadapu, Puneeth; Ainavolu, Vinay; Sangal, Rajeev

doi:10.1109/ialp.2012.16

Cited by 21 publications

(14 citation statements)

References 4 publications

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“…The main drawback of using this kind of resolution is its low precision. Abhijeet Gupta et al [15] proposed the syntactic parser that uses the Computational Paninian Grammar (CPG) framework. Limitations of this system is that aggregation operators and Join are not supported also the dependency relations are syntactico-semantic in nature.…”

Section: Literature Surveymentioning

confidence: 99%

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

Kokare¹,

Wanjale²

2015

IJMSC

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A natural language query builder interface retrieves the required data in structured form from database when query is entered in natural language. The user need not necessarily have sufficient technical knowledge of structured query language statements so nontechnical users can also use this proposed model. In natural language parsing, getting highly accurate syntactic analysis is a crucial step. Parsing of natural languages is the process of mapping an input string or a natural language sentence to its syntactic representation. Constituency parsing approach takes more time for parsing. So, natural language query builder interface is developed in which the parsing of natural language sentence is done by using dependency parsing approach. Dependency parsing technique is widespread in natural language domain because of its state-of-art accuracy and efficiency and also it performs best. In this paper, the buffering scheme is also proposed for natural language statements which will not load the whole sentence if it was done previously. Also there was a need of generalized access to all tables from database which is handled in this system.

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Section: Literature Surveymentioning

confidence: 99%

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

Kokare¹,

Wanjale²

2015

IJMSC

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“…A novel approach to building NLIDB is presented in [Gupta et al 2012]. The approach is based on dependency trees using Computational Paninian Grammar (CPG) [Bharati et al 2014] in which the relationships are syntactic-semantic.…”

Section: Introductionmentioning

confidence: 99%

Empowering Natural Language Interfaces to Databases with Aggregations

Novello

Casanova

2021

jidm

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A Natural Language Interface to Database (NLIDB) refers to a database interface that translates a question asked in natural language into a structured query. Aggregation questions express aggregation functions, such as count, sum, average, minimum and maximum, and optionally a group by clause and a having clause. NLIDBs deliver good results for standard questions but usually do not deal with aggregation questions. The main contribution of this article is a generic module, called GLAMORISE (GeneraL Aggregation MOdule using a RelatIonal databaSE), that extends NLIDBs to cope with aggregation questions. GLAMORISE covers aggregations with ambiguities, timescale differences, aggregations in multiple attributes, the use of superlative adjectives, basic recognition of measurement units, and aggregations in attributes with compound names.

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“…This is a programme that has as input an NL query and as output a syntactic representation which facilitates the mapping to a database query language (Li and Jagadish, 2014). Other works in this category are semantic grammar-based systems (Giordani and Moschitti, 2010; Gupta et al , 2012). The result of a semantic grammar parser is similar to a syntax parser by giving a tree representation.…”

Section: Introductionmentioning

confidence: 99%

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

Kamal¹,

Benchikha²

2017

JEIM

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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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A Novel Approach Towards Building a Portable NLIDB System Using the Computational Paninian Grammar Framework

Cited by 21 publications

References 4 publications

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

A Natural Language Query Builder Interface for Structured Databases Using Dependency Parsing

Empowering Natural Language Interfaces to Databases with Aggregations

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

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