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2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)最新文献

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Language Identification of Hindi-English tweets using code-mixed BERT 用代码混合BERT对印英推文进行语言识别
2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) Pub Date : 2021-07-02 DOI: 10.1109/ICCICC53683.2021.9811292
M. Z. Ansari, M. Beg, Tanvir Ahmad, Mohd Jazib Khan, Ghazali Wasim
{"title":"Language Identification of Hindi-English tweets using code-mixed BERT","authors":"M. Z. Ansari, M. Beg, Tanvir Ahmad, Mohd Jazib Khan, Ghazali Wasim","doi":"10.1109/ICCICC53683.2021.9811292","DOIUrl":"https://doi.org/10.1109/ICCICC53683.2021.9811292","url":null,"abstract":"Language identification of social media text has been an interesting problem of study in recent years. Social media messages are predominantly in code mixed in non-English speaking states. Prior knowledge by pre-training contextual embeddings have shown state of the art results for a range of downstream tasks. Recently, models such as Bidirectional Encoder Representations from Transformers (BERT) have shown that using a large amount of unlabeled data, the pre-trained language models are even more beneficial for learning common language representations. Extensive experiments exploiting transfer learning and fine-tuning BERT models to identify language on Twitter are presented in this paper. The work utilizes a data collection of Hindi-English-Urdu code-mixed text for language pre-training and Hindi-English code-mixed for subsequent word-level language classification. The results show that the representations pre-trained over code-mixed data produce better results by their monolingual counterpart.","PeriodicalId":101653,"journal":{"name":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128890763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
Real-Time Cognitive Evaluation of Online Learners through Automatically Generated Questions 通过自动生成问题对在线学习者进行实时认知评估
2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) Pub Date : 2021-06-06 DOI: 10.1109/ICCICC53683.2021.9811326
Ritu Gala, Revathi Vijayaraghavan, V. Nikam, A. Kiwelekar
{"title":"Real-Time Cognitive Evaluation of Online Learners through Automatically Generated Questions","authors":"Ritu Gala, Revathi Vijayaraghavan, V. Nikam, A. Kiwelekar","doi":"10.1109/ICCICC53683.2021.9811326","DOIUrl":"https://doi.org/10.1109/ICCICC53683.2021.9811326","url":null,"abstract":"With the increased adoption of E-learning platforms, keeping online learners engaged throughout a lesson is challenging. One approach to tackle this challenge is to probe learners periodically by asking questions. The paper presents an approach to generate questions from a given video lecture automatically. The generated questions are aimed to evaluate learners' lower-level cognitive abilities. The approach automatically extracts text from video lectures to generate wh-kinds of questions. When learners respond with an answer, the proposed approach further evaluates the response and provides feedback. Besides enhancing learner's engagement, this approach's main benefits are that it frees instructors from designing questions to check the comprehension of a topic. Thus, instructors can spend this time productively on other activities.","PeriodicalId":101653,"journal":{"name":"2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114098413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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