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http://hdl.handle.net/1893/27750
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Alqarafi, Abdulrahman S | en_UK |
dc.contributor.author | Adeel, Ahsan | en_UK |
dc.contributor.author | Gogate, Mandar | en_UK |
dc.contributor.author | Dashtipour, Kia | en_UK |
dc.contributor.author | Hussain, Amir | en_UK |
dc.contributor.author | Durrani, Tariq | en_UK |
dc.contributor.editor | Liang, Q | en_UK |
dc.contributor.editor | Mu, J | en_UK |
dc.contributor.editor | Jia, M | en_UK |
dc.contributor.editor | Wang, W | en_UK |
dc.contributor.editor | Feng, X | en_UK |
dc.contributor.editor | Zhang, B | en_UK |
dc.date.accessioned | 2018-09-07T16:58:39Z | - |
dc.date.available | 2018-09-07T16:58:39Z | - |
dc.date.issued | 2019-12-31 | en_UK |
dc.identifier.uri | http://hdl.handle.net/1893/27750 | - |
dc.description.abstract | In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information sharing platforms. Apart from these, a collection of product reviews, facts, poll information, etc., is a need for every company or organization ranging from start-ups to big firms and governments. Clearly, it is very challenging to analyse such big data to improve products, services, and satisfy customer requirements. Therefore, it is necessary to automate the evaluation process using advanced sentiment analysis techniques. Most of previous works focused on uni-modal sentiment analysis mainly textual model. In this paper, a novel Arabic multimodal dataset is presented and validated using state-of-the-art support vector machine (SVM) based classification method. | en_UK |
dc.language.iso | en | en_UK |
dc.publisher | Springer | en_UK |
dc.relation | Alqarafi AS, Adeel A, Gogate M, Dashtipour K, Hussain A & Durrani T (2019) Towards Arabic multi-modal sentiment analysis. In: Liang Q, Mu J, Jia M, Wang W, Feng X & Zhang B (eds.) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, 463. CSPS 2017: Communications, Signal Processing, and Systems, 14.07.2017-16.07.2017. Harbin, China: Springer, pp. 2378-2386. https://doi.org/10.1007/978-981-10-6571-2_290 | en_UK |
dc.relation.ispartofseries | Lecture Notes in Electrical Engineering, 463 | en_UK |
dc.rights | Accepted for publication in Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, 463. CSPS 2017: Communications, Signal Processing, and Systems, Harbin, China, 14.07.2017-16.07.2017. Harbin, China: Springer Verlag, pp. 2378-2386. The final publication is available at Springer via https://doi.org/10.1007/978-981-10-6571-2_290. | en_UK |
dc.subject | Arabic | en_UK |
dc.subject | Sentiment analysis | en_UK |
dc.subject | Multi-modal | en_UK |
dc.title | Towards Arabic multi-modal sentiment analysis | en_UK |
dc.type | Conference Paper | en_UK |
dc.identifier.doi | 10.1007/978-981-10-6571-2_290 | en_UK |
dc.citation.jtitle | Lecture Notes in Electrical Engineering | en_UK |
dc.citation.issn | 1876-1100 | en_UK |
dc.citation.spage | 2378 | en_UK |
dc.citation.epage | 2386 | en_UK |
dc.citation.publicationstatus | Published | en_UK |
dc.type.status | AM - Accepted Manuscript | en_UK |
dc.contributor.funder | Engineering and Physical Sciences Research Council | en_UK |
dc.citation.btitle | Communications, Signal Processing, and Systems. CSPS 2017 | en_UK |
dc.citation.conferencedates | 2017-07-14 - 2017-07-16 | en_UK |
dc.citation.conferencename | CSPS 2017: Communications, Signal Processing, and Systems | en_UK |
dc.citation.date | 07/06/2018 | en_UK |
dc.citation.isbn | 978-981-10-6570-5; 978-981-10-6571-2 | en_UK |
dc.publisher.address | Harbin, China | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.contributor.affiliation | Computing Science | en_UK |
dc.identifier.isi | WOS:000448618900290 | en_UK |
dc.identifier.scopusid | 2-s2.0-85048666341 | en_UK |
dc.identifier.wtid | 943486 | en_UK |
dc.contributor.orcid | 0000-0003-1712-9014 | en_UK |
dc.contributor.orcid | 0000-0001-8651-5117 | en_UK |
dc.contributor.orcid | 0000-0002-8080-082X | en_UK |
dc.date.accepted | 2017-06-15 | en_UK |
dcterms.dateAccepted | 2017-06-15 | en_UK |
dc.date.filedepositdate | 2018-09-07 | en_UK |
dc.relation.funderproject | Towards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devices | en_UK |
dc.relation.funderref | EP/M026981/1 | en_UK |
rioxxterms.apc | not required | en_UK |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_UK |
rioxxterms.version | AM | en_UK |
local.rioxx.author | Alqarafi, Abdulrahman S| | en_UK |
local.rioxx.author | Adeel, Ahsan| | en_UK |
local.rioxx.author | Gogate, Mandar|0000-0003-1712-9014 | en_UK |
local.rioxx.author | Dashtipour, Kia|0000-0001-8651-5117 | en_UK |
local.rioxx.author | Hussain, Amir|0000-0002-8080-082X | en_UK |
local.rioxx.author | Durrani, Tariq| | en_UK |
local.rioxx.project | EP/M026981/1|Engineering and Physical Sciences Research Council|http://dx.doi.org/10.13039/501100000266 | en_UK |
local.rioxx.contributor | Liang, Q| | en_UK |
local.rioxx.contributor | Mu, J| | en_UK |
local.rioxx.contributor | Jia, M| | en_UK |
local.rioxx.contributor | Wang, W| | en_UK |
local.rioxx.contributor | Feng, X| | en_UK |
local.rioxx.contributor | Zhang, B| | en_UK |
local.rioxx.freetoreaddate | 2018-09-07 | en_UK |
local.rioxx.licence | http://www.rioxx.net/licenses/all-rights-reserved|2018-09-07| | en_UK |
local.rioxx.filename | Abdulrahman Alqarafi CSPS Paper.pdf | en_UK |
local.rioxx.filecount | 1 | en_UK |
local.rioxx.source | 978-981-10-6570-5; 978-981-10-6571-2 | en_UK |
Appears in Collections: | Computing Science and Mathematics Conference Papers and Proceedings |
Files in This Item:
File | Description | Size | Format | |
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Abdulrahman Alqarafi CSPS Paper.pdf | Fulltext - Accepted Version | 427.88 kB | Adobe PDF | View/Open |
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