{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T13:33:51Z","timestamp":1750858431977,"version":"3.41.0"},"reference-count":31,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T00:00:00Z","timestamp":1705276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2024,1,31]]},"abstract":"<jats:p>\n            The rapid growth of Web 2.0, which enables people to generate, communicate, and share information, has resulted in an increase in the total number of users. In developing countries, online users\u2019 sentiment influences decision-making, social views, individual consumption decisions, and entity quality monitoring. As a result, more accurate sentiment analysis, particularly in their native language such as Hindi, is preferred over crude binary categorization. This is because of the abundance of web-based data in Indian languages such as Hindi, Marathi, Kannada, Tamil, and so on. Analyzing this data and recovering valuable and relevant information from handwritten text has become extremely important. Despite years of research and development, no\n            <jats:bold>optical writing recognition (OCR)<\/jats:bold>\n            system has ever been certified as completely reliable. The first step in any pattern recognition system is feature selection. In many fields, feature selection is studied as a combinatorial optimization problem. The primary goal of feature selection is to reduce the number of redundant and ineffective traits in the recognition system. This feature selection is used to maintain or improve the performance of the classifier used by the recognition system: A\n            <jats:bold>support vector machine (SVM)<\/jats:bold>\n            technique could be used to solve this character recognition problem. The Hindi character recognition system recognizes Hindi characters by employing morphological operations, edge detection, HOG feature extraction, and an SVM-based classifier. The proposed model outperformed the current state-of-the-art method, achieving an accuracy of 96.77%.\n          <\/jats:p>","DOI":"10.1145\/3557895","type":"journal-article","created":{"date-parts":[[2022,10,6]],"date-time":"2022-10-06T12:19:22Z","timestamp":1665058762000},"page":"1-22","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Semantic and Context Understanding for Sentiment Analysis in Hindi Handwritten Character Recognition Using a Multiresolution Technique"],"prefix":"10.1145","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7945-4616","authenticated-orcid":false,"given":"Ankit","family":"Kumar","sequence":"first","affiliation":[{"name":"GLA University, Mathura"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3097-6568","authenticated-orcid":false,"given":"Surbhi","family":"Bhatia","sequence":"additional","affiliation":[{"name":"King Faisal University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2029-5067","authenticated-orcid":false,"given":"Mohammad R.","family":"Khosravi","sequence":"additional","affiliation":[{"name":"Persian Gulf University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0612-6005","authenticated-orcid":false,"given":"Arwa","family":"Mashat","sequence":"additional","affiliation":[{"name":"King Abdulaziz University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7297-335X","authenticated-orcid":false,"given":"Parul","family":"Agarwal","sequence":"additional","affiliation":[{"name":"Jamia Hamdard"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,1,15]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.47836\/pjst.29.1.25"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2020.107260"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.02.093"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3025823"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.4018\/IJSDA.20211001.oa16"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1515\/jisys-2018-0475"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3447735"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.32604\/csse.2022.024059"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485242"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1145\/3383330"},{"key":"e_1_3_1_12_2","volume-title":"2015 4th International Symposium on Emerging Trends and Technologies in Libraries and Information Services","author":"Gaur Akanksha","year":"2015","unstructured":"Akanksha Gaur and Sunita Yadav. 2015. Handwritten Hindi character recognition using k-means clustering and SVM. In 2015 4th International Symposium on Emerging Trends and Technologies in Libraries and Information Services. IEEE."},{"key":"e_1_3_1_13_2","doi-asserted-by":"publisher","DOI":"10.1145\/3450447"},{"key":"e_1_3_1_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106198"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1142\/S0218213020500141"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCC.2010.2095841"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/CCAA.2015.7148550"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/3469722"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3461764"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1145\/3469891"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.18280\/ts.390302"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-189869"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3075774"},{"issue":"21","key":"e_1_3_1_24_2","first-page":"2641","article-title":"Aspect-based sentiment analysis in Hindi language by ensembling pre-trained mBERT models","volume":"10","author":"Pathak Abhilash","year":"2021","unstructured":"Abhilash Pathak, Sudhanshu Kumar, Partha Roy, and Byung-Gyu Kim. 2021. Aspect-based sentiment analysis in Hindi language by ensembling pre-trained mBERT models. Electronics (Basel) 10, 21 (2021), 2641.","journal-title":"Electronics (Basel)"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13278-022-00877-w"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1080\/19472498.2021.1878787"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3150172"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485243"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12046-020-01424-z"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-020-09730-x"},{"issue":"6","key":"e_1_3_1_31_2","first-page":"954","article-title":"A sentiment analysis system for the Hindi language by integrating Gated Recurrent Unit with Genetic Algorithm","volume":"17","author":"Shrivastava Kush","year":"2020","unstructured":"Kush Shrivastava and Shishir Kumar. 2020. A sentiment analysis system for the Hindi language by integrating Gated Recurrent Unit with Genetic Algorithm. Int. Arab J. Inf. Technol. 17, 6 (2020), 954\u2013964.","journal-title":"Int. Arab J. Inf. 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