BiLSTM-based Approach to the Natural Language Text Dependencies Analysis

This article discusses the idea of conducting a multistage process of building a search image of a query in natural language for use in the semantic search system. Modern methods and tools for processing natural language are widely used in the field of machine translation. Research on search engines...

Full description

Saved in:
Bibliographic Details
Main Author: A. Chernyshov
Format: Article
Language:Russian
Published: International Centre for Scientific and Technical Information (ICSTI) 2019-03-01
Series:Informaciâ i Innovacii
Subjects:
Online Access:https://journal.icsti.int/jour/article/view/113
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850074579268009984
author A. Chernyshov
author_facet A. Chernyshov
author_sort A. Chernyshov
collection DOAJ
description This article discusses the idea of conducting a multistage process of building a search image of a query in natural language for use in the semantic search system. Modern methods and tools for processing natural language are widely used in the field of machine translation. Research on search engines and semantic search mainly focuses on data storage and further analysis. Most search engines use a huge amount of previously accumulated user queries to predict search results, without taking into account the user’s intention through quality query processing. The proposed approach is based on the selection of the maximum amount of information from the original request by means of syntactic and semantic analysis, as well as the use of synonymous extension techniques. This article describes the first step in the process of building a search query model, based on extracting syntactic dependencies from the original sentence.
format Article
id doaj-art-8f099e77795646bba7f91c7f268f6db8
institution DOAJ
issn 1994-2443
language Russian
publishDate 2019-03-01
publisher International Centre for Scientific and Technical Information (ICSTI)
record_format Article
series Informaciâ i Innovacii
spelling doaj-art-8f099e77795646bba7f91c7f268f6db82025-08-20T02:46:32ZrusInternational Centre for Scientific and Technical Information (ICSTI)Informaciâ i Innovacii1994-24432019-03-01141444710.31432/1994-2443-2019-14-1-44-47112BiLSTM-based Approach to the Natural Language Text Dependencies AnalysisA. Chernyshov0National research nuclear University MEPhIThis article discusses the idea of conducting a multistage process of building a search image of a query in natural language for use in the semantic search system. Modern methods and tools for processing natural language are widely used in the field of machine translation. Research on search engines and semantic search mainly focuses on data storage and further analysis. Most search engines use a huge amount of previously accumulated user queries to predict search results, without taking into account the user’s intention through quality query processing. The proposed approach is based on the selection of the maximum amount of information from the original request by means of syntactic and semantic analysis, as well as the use of synonymous extension techniques. This article describes the first step in the process of building a search query model, based on extracting syntactic dependencies from the original sentence.https://journal.icsti.int/jour/article/view/113searchquerydependenciesneural network
spellingShingle A. Chernyshov
BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
Informaciâ i Innovacii
search
query
dependencies
neural network
title BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
title_full BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
title_fullStr BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
title_full_unstemmed BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
title_short BiLSTM-based Approach to the Natural Language Text Dependencies Analysis
title_sort bilstm based approach to the natural language text dependencies analysis
topic search
query
dependencies
neural network
url https://journal.icsti.int/jour/article/view/113
work_keys_str_mv AT achernyshov bilstmbasedapproachtothenaturallanguagetextdependenciesanalysis