research-article

Natural Language Agreement in the Generation Mechanism based on Stratified Graphs

Authors:

Gheorghe Grigoraş,

Daniela DănciulescuAuthors Info & Claims

BCI '15: Proceedings of the 7th Balkan Conference on Informatics Conference

Article No.: 36, Pages 1 - 8

https://doi.org/10.1145/2801081.2801121

Published: 02 September 2015 Publication History

Abstract

A Stratified Graph can generate natural language constructions by acting as a transition network with arc labels referring to word categories and word forms. In this representation, each grammar rule can be transposed in a sequence of labeled paths. The generation mechanism defined by means of stratified graph uses a bottom-up approach. The advantage of this generation mechanism relies on its bottom-up approach characteristic: this mechanism never suggests constructions that are not correct based on the involved representation elements. As it will be presented, implementing syntactic agreement rules in this natural language generation mechanism can determine different results even if identical words are considered in the generation mechanism.

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Cited By

Smarandache FColhon MVlăduţescu ŞNegrea X(2019)Word-level neutrosophic sentiment similarityApplied Soft Computing10.1016/j.asoc.2019.03.03480:C(167-176)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1016/j.asoc.2019.03.034
Saeed A(2018)Recent neutrosophic models for KRP systems2018 7th International Conference on Computers Communications and Control (ICCCC)10.1109/ICCCC.2018.8390440(76-81)Online publication date: May-2018
https://doi.org/10.1109/ICCCC.2018.8390440

Natural Language Agreement in the Generation Mechanism based on Stratified Graphs
1. Computing methodologies
  1. Artificial intelligence

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cover image ACM Other conferences

BCI '15: Proceedings of the 7th Balkan Conference on Informatics Conference

September 2015

293 pages

ISBN:9781450333351

DOI:10.1145/2801081

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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UCV: University of Craiova

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New York, NY, United States

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Published: 02 September 2015

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BCI '15

BCI '15: 7th Balkan Conference in Informatics

September 2 - 4, 2015

Craiova, Romania

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BCI '15 Paper Acceptance Rate 32 of 74 submissions, 43%;

Overall Acceptance Rate 97 of 250 submissions, 39%

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Cited By

Smarandache FColhon MVlăduţescu ŞNegrea X(2019)Word-level neutrosophic sentiment similarityApplied Soft Computing10.1016/j.asoc.2019.03.03480:C(167-176)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1016/j.asoc.2019.03.034
Saeed A(2018)Recent neutrosophic models for KRP systems2018 7th International Conference on Computers Communications and Control (ICCCC)10.1109/ICCCC.2018.8390440(76-81)Online publication date: May-2018
https://doi.org/10.1109/ICCCC.2018.8390440

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