Text sentiment analysis method and system based on graph convolution network and electronic device

The invention relates to a text sentiment analysis method and system based on a graph convolution network and an electronic device. The method comprises the steps: word segmentation being conducted onan input text sequence; converting each segmented word into a corresponding word embedding according...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: PU LUWEN, ZOU YUEXIAN
Format: Patent
Sprache:chi ; eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator PU LUWEN
ZOU YUEXIAN
description The invention relates to a text sentiment analysis method and system based on a graph convolution network and an electronic device. The method comprises the steps: word segmentation being conducted onan input text sequence; converting each segmented word into a corresponding word embedding according to the sequence of the text sequence; extracting a forward semantic feature and a reverse semanticfeature of each word embedding, and combining the forward semantic features and the reverse semantic features at the same positions to obtain a context semantic feature of each word embedding; according to the context semantic feature of each word embedding, calculating a semantic relationship value between any two word embedding to obtain a connection matrix; analyzing a dependency syntax tree of the text sequence according to the connection matrix; performing graph convolution operation by taking the dependency syntax tree as a graph to obtain dependency vectors of ROOT nodes of the dependency syntax tree; and perfo
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN112035661A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN112035661A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN112035661A3</originalsourceid><addsrcrecordid>eNqNizEKwkAURNNYiHqH7wEEYzC9BMXKKn3Y7I66uNkf8r_R3N5FPIDNDPN4M8_aGm8lQVTfpSATTZjEC3XQO7u0Hckkio5aI3DEkW6D6e9kOY4cnuoTidAXD4-vjQCrA0dvyWH0FstsdjVBsPr1IlufjnV13qDnBtIbi_Rvqkue77bFvizzQ_GP8wGhjT6X</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Text sentiment analysis method and system based on graph convolution network and electronic device</title><source>esp@cenet</source><creator>PU LUWEN ; ZOU YUEXIAN</creator><creatorcontrib>PU LUWEN ; ZOU YUEXIAN</creatorcontrib><description>The invention relates to a text sentiment analysis method and system based on a graph convolution network and an electronic device. The method comprises the steps: word segmentation being conducted onan input text sequence; converting each segmented word into a corresponding word embedding according to the sequence of the text sequence; extracting a forward semantic feature and a reverse semanticfeature of each word embedding, and combining the forward semantic features and the reverse semantic features at the same positions to obtain a context semantic feature of each word embedding; according to the context semantic feature of each word embedding, calculating a semantic relationship value between any two word embedding to obtain a connection matrix; analyzing a dependency syntax tree of the text sequence according to the connection matrix; performing graph convolution operation by taking the dependency syntax tree as a graph to obtain dependency vectors of ROOT nodes of the dependency syntax tree; and perfo</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2020</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20201204&amp;DB=EPODOC&amp;CC=CN&amp;NR=112035661A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20201204&amp;DB=EPODOC&amp;CC=CN&amp;NR=112035661A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>PU LUWEN</creatorcontrib><creatorcontrib>ZOU YUEXIAN</creatorcontrib><title>Text sentiment analysis method and system based on graph convolution network and electronic device</title><description>The invention relates to a text sentiment analysis method and system based on a graph convolution network and an electronic device. The method comprises the steps: word segmentation being conducted onan input text sequence; converting each segmented word into a corresponding word embedding according to the sequence of the text sequence; extracting a forward semantic feature and a reverse semanticfeature of each word embedding, and combining the forward semantic features and the reverse semantic features at the same positions to obtain a context semantic feature of each word embedding; according to the context semantic feature of each word embedding, calculating a semantic relationship value between any two word embedding to obtain a connection matrix; analyzing a dependency syntax tree of the text sequence according to the connection matrix; performing graph convolution operation by taking the dependency syntax tree as a graph to obtain dependency vectors of ROOT nodes of the dependency syntax tree; and perfo</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizEKwkAURNNYiHqH7wEEYzC9BMXKKn3Y7I66uNkf8r_R3N5FPIDNDPN4M8_aGm8lQVTfpSATTZjEC3XQO7u0Hckkio5aI3DEkW6D6e9kOY4cnuoTidAXD4-vjQCrA0dvyWH0FstsdjVBsPr1IlufjnV13qDnBtIbi_Rvqkue77bFvizzQ_GP8wGhjT6X</recordid><startdate>20201204</startdate><enddate>20201204</enddate><creator>PU LUWEN</creator><creator>ZOU YUEXIAN</creator><scope>EVB</scope></search><sort><creationdate>20201204</creationdate><title>Text sentiment analysis method and system based on graph convolution network and electronic device</title><author>PU LUWEN ; ZOU YUEXIAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN112035661A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2020</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>PU LUWEN</creatorcontrib><creatorcontrib>ZOU YUEXIAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>PU LUWEN</au><au>ZOU YUEXIAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Text sentiment analysis method and system based on graph convolution network and electronic device</title><date>2020-12-04</date><risdate>2020</risdate><abstract>The invention relates to a text sentiment analysis method and system based on a graph convolution network and an electronic device. The method comprises the steps: word segmentation being conducted onan input text sequence; converting each segmented word into a corresponding word embedding according to the sequence of the text sequence; extracting a forward semantic feature and a reverse semanticfeature of each word embedding, and combining the forward semantic features and the reverse semantic features at the same positions to obtain a context semantic feature of each word embedding; according to the context semantic feature of each word embedding, calculating a semantic relationship value between any two word embedding to obtain a connection matrix; analyzing a dependency syntax tree of the text sequence according to the connection matrix; performing graph convolution operation by taking the dependency syntax tree as a graph to obtain dependency vectors of ROOT nodes of the dependency syntax tree; and perfo</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN112035661A
source esp@cenet
subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
title Text sentiment analysis method and system based on graph convolution network and electronic device
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T08%3A10%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=PU%20LUWEN&rft.date=2020-12-04&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN112035661A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true