FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2913243196> ?p ?o ?g. }

• W2913243196 abstract "The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue that these two important properties can play a major role in Chinese sentiment analysis. Particularly, we propose two effective features to encode phonetic information. Next, we develop a Disambiguate Intonation for Sentiment Analysis (DISA) network using a reinforcement network. It functions as disambiguating intonations for each Chinese character (pinyin). Thus, a precise phonetic representation of Chinese is learned. Furthermore, we also fuse phonetic features with textual and visual features in order to mimic the way humans read and understand Chinese text. Experimental results on five different Chinese sentiment analysis datasets show that the inclusion of phonetic features significantly and consistently improves the performance of textual and visual representations and outshines the state-of-the-art Chinese character level representations." @default.
• W2913243196 created "2019-02-21" @default.
• W2913243196 creator A5000940158 @default.
• W2913243196 creator A5025038200 @default.
• W2913243196 creator A5033376109 @default.
• W2913243196 creator A5052327236 @default.
• W2913243196 creator A5064842058 @default.
• W2913243196 date "2019-01-23" @default.
• W2913243196 modified "2023-09-27" @default.
• W2913243196 title "Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning" @default.
• W2913243196 cites W1501931667 @default.
• W2913243196 cites W1594229598 @default.
• W2913243196 cites W1826029799 @default.
• W2913243196 cites W1982498087 @default.
• W2913243196 cites W1989085630 @default.
• W2913243196 cites W2001970020 @default.
• W2913243196 cites W2016053056 @default.
• W2913243196 cites W2085662862 @default.
• W2913243196 cites W2103070508 @default.
• W2913243196 cites W2118652393 @default.
• W2913243196 cites W2118952344 @default.
• W2913243196 cites W2119717200 @default.
• W2913243196 cites W2132339004 @default.
• W2913243196 cites W2136655611 @default.
• W2913243196 cites W2146026051 @default.
• W2913243196 cites W2155027007 @default.
• W2913243196 cites W2166706824 @default.
• W2913243196 cites W2250539671 @default.
• W2913243196 cites W2250966211 @default.
• W2913243196 cites W2251131401 @default.
• W2913243196 cites W2308045930 @default.
• W2913243196 cites W2358307482 @default.
• W2913243196 cites W2394700483 @default.
• W2913243196 cites W2470673105 @default.
• W2913243196 cites W2481359644 @default.
• W2913243196 cites W2493920898 @default.
• W2913243196 cites W2500392116 @default.
• W2913243196 cites W2566150155 @default.
• W2913243196 cites W2584561145 @default.
• W2913243196 cites W2606776062 @default.
• W2913243196 cites W2731114144 @default.
• W2913243196 cites W2740550900 @default.
• W2913243196 cites W2745862583 @default.
• W2913243196 cites W2765369538 @default.
• W2913243196 cites W2766718178 @default.
• W2913243196 cites W2767058267 @default.
• W2913243196 cites W2767849480 @default.
• W2913243196 cites W2771833219 @default.
• W2913243196 cites W2780698117 @default.
• W2913243196 cites W2785128315 @default.
• W2913243196 cites W2788009253 @default.
• W2913243196 cites W2788967885 @default.
• W2913243196 cites W2790250716 @default.
• W2913243196 cites W2887856105 @default.
• W2913243196 cites W2899099710 @default.
• W2913243196 cites W2949541494 @default.
• W2913243196 cites W2950577311 @default.
• W2913243196 cites W2952935105 @default.
• W2913243196 cites W2962951088 @default.
• W2913243196 cites W2963520511 @default.
• W2913243196 cites W2963710346 @default.
• W2913243196 cites W2964010806 @default.
• W2913243196 cites W2964164368 @default.
• W2913243196 cites W2964325863 @default.
• W2913243196 cites W644347516 @default.
• W2913243196 doi "https://doi.org/10.48550/arxiv.1901.07880" @default.
• W2913243196 hasPublicationYear "2019" @default.
• W2913243196 type Work @default.
• W2913243196 sameAs 2913243196 @default.
• W2913243196 citedByCount "0" @default.
• W2913243196 crossrefType "posted-content" @default.
• W2913243196 hasAuthorship W2913243196A5000940158 @default.
• W2913243196 hasAuthorship W2913243196A5025038200 @default.
• W2913243196 hasAuthorship W2913243196A5033376109 @default.
• W2913243196 hasAuthorship W2913243196A5052327236 @default.
• W2913243196 hasAuthorship W2913243196A5064842058 @default.
• W2913243196 hasBestOaLocation W29132431961 @default.
• W2913243196 hasConcept C138885662 @default.
• W2913243196 hasConcept C150670947 @default.
• W2913243196 hasConcept C154945302 @default.
• W2913243196 hasConcept C17744445 @default.
• W2913243196 hasConcept C199539241 @default.
• W2913243196 hasConcept C204321447 @default.
• W2913243196 hasConcept C2524010 @default.
• W2913243196 hasConcept C2776359362 @default.
• W2913243196 hasConcept C2780844864 @default.
• W2913243196 hasConcept C2780861071 @default.
• W2913243196 hasConcept C2781045179 @default.
• W2913243196 hasConcept C2781051154 @default.
• W2913243196 hasConcept C2781095461 @default.
• W2913243196 hasConcept C33923547 @default.
• W2913243196 hasConcept C41008148 @default.
• W2913243196 hasConcept C41895202 @default.
• W2913243196 hasConcept C554936623 @default.
• W2913243196 hasConcept C94625758 @default.
• W2913243196 hasConceptScore W2913243196C138885662 @default.
• W2913243196 hasConceptScore W2913243196C150670947 @default.
• W2913243196 hasConceptScore W2913243196C154945302 @default.
• W2913243196 hasConceptScore W2913243196C17744445 @default.
• W2913243196 hasConceptScore W2913243196C199539241 @default.

• next