{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T21:48:35Z","timestamp":1784843315568,"version":"3.55.0"},"reference-count":22,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,7,15]],"date-time":"2021-07-15T00:00:00Z","timestamp":1626307200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFA0909100"],"award-info":[{"award-number":["2020YFA0909100"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902385"],"award-info":[{"award-number":["61902385"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,15]]},"DOI":"10.1109\/rcar52367.2021.9517671","type":"proceedings-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T20:32:50Z","timestamp":1630441970000},"page":"590-595","source":"Crossref","is-referenced-by-count":13,"title":["WRS: A Novel Word-embedding Method for Real-time Sentiment with Integrated LSTM-CNN Model"],"prefix":"10.1109","author":[{"given":"Abdur","family":"Rasool","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingshan","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Qu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaojie","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3056664"},{"key":"ref11","article-title":"Convolutional sequence to sequence learning","author":"gehring","year":"2017","journal-title":"ArXiv"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3010802"},{"key":"ref13","first-page":"142","article-title":"Learning word vectors for sentiment analysis","volume":"1","author":"maas","year":"0","journal-title":"Proc 49th Annu Meeting Assoc Comput Linguist Human Lang Technol 2011"},{"key":"ref14","first-page":"2200","article-title":"SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining","volume":"10","author":"baccianella","year":"0","journal-title":"Proceeidngs of the LREC"},{"key":"ref15","article-title":"NRC-Canada: Building the state of-the-art in sentiment analysis of tweets","author":"mohammad","year":"2013","journal-title":"ArXiv"},{"key":"ref16","first-page":"2666","article-title":"SenticNet 4: a semantic resource for sentiment analysis based on conceptual primitives","author":"cambria","year":"0","journal-title":"Proceedings of the COLING"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2807452"},{"key":"ref18","article-title":"Wordrank: Learning word embeddings via robust ranking","author":"ji","year":"2015","journal-title":"ArXiv"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2019.2959624"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09632-9"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICCCNT.2013.6726818"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47602-5_40"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2019.08.153"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref7","article-title":"word2vec Parameter Learning Explained","author":"rong","year":"0","journal-title":"ArXiv"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781139084789.001"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2019.10.012"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2985228"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-020-02163-8"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1176\/2\/022015"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3030642"}],"event":{"name":"2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)","location":"Xining, China","start":{"date-parts":[[2021,7,15]]},"end":{"date-parts":[[2021,7,19]]}},"container-title":["2021 IEEE International Conference on Real-time Computing and Robotics (RCAR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9517075\/9517076\/09517671.pdf?arnumber=9517671","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:45:01Z","timestamp":1652197501000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9517671\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,15]]},"references-count":22,"URL":"https:\/\/doi.org\/10.1109\/rcar52367.2021.9517671","relation":{},"subject":[],"published":{"date-parts":[[2021,7,15]]}}}