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  • Search: isPartOf:"Data Technologies and Applications"
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Subject
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Machine learning 18 Deep learning 14 Text mining 13 Data mining 9 Sentiment analysis 7 Social media 7 Big data 6 Knowledge management 6 BERT 5 CNN 5 COVID-19 5 Classification 5 Neural network 5 Ontology 5 Transfer learning 5 Clustering 4 Deep belief network 4 LSTM 4 Topic model 4 Attention mechanism 3 Convolutional neural network 3 Data analysis 3 Data science 3 Decision tree 3 ECG 3 GWO 3 Latent Dirichlet allocation 3 Literature review 3 Natural language processing 3 Optimization 3 Random forest 3 Recommender system 3 Recommender systems 3 Recurrent neural network 3 Regression 3 Review helpfulness 3 Social network 3 Social network analysis 3 Topic detection 3 Twitter 3
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Online availability
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Undetermined 243 Free 6 CC license 5
Type of publication
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Article 249
Type of publication (narrower categories)
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research-article 231 review 9 technical-paper 4 back-matter 2 case-report 2 editorial 1
Language
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English 249
Author
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Nagwani, Naresh Kumar 5 Pereira, Valdecy 5 Arasteh, Bahman 4 Bao, Zheshi 3 Du, Xu 3 Idri, Ali 3 Janghel, Rekh Ram 3 Lee, Changro 3 Sisodia, Dilip Singh 3 Swetapadma, Aleena 3 Wang, Bin 3 Wang, Hei-Chia 3 Zhang, Qian 3 Abbasi, Amir Zaib 2 Abu Bakar, Azuraliza 2 Alhalabi, Wadee 2 Basilio, Marcio Pereira 2 Bhattacharya, Riju 2 D, Binu 2 Dang, Depeng 2 Garoufallou, Emmanouel 2 Hung, Jui-Long 2 Jeon, Jeonghwan 2 Khalid, Shah 2 Kim, Jaekyeong 2 Li, Ming 2 Li, Qinglong 2 Li, Tingting 2 Liu, Duen-Ren 2 P, Vijaya 2 Park, Jaeseung 2 Roman, Dumitru 2 Sahu, Satya Prakash 2 Schöpfel, Joachim 2 Singh, Lokesh 2 Sinha, Prashant Kumar 2 Sisodia, Deepti 2 Siyal, Abdul Waheed 2 Soylu, Ahmet 2 Suh, Yongmoo 2
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Data Technologies and Applications 249
Source
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Other ZBW resources 249
Showing 61 - 70 of 249
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Optimized aspect and self-attention aware LSTM for target-based semantic analysis (OAS-LSTM-TSA)
Vasavi, B.; Dileep, P.; Srinivasarao, Ulligaddala - In: Data Technologies and Applications 58 (2023) 3, pp. 447-471
Purpose Aspect-based sentiment analysis (ASA) is a task of sentiment analysis that requires predicting aspect sentiment polarity for a given sentence. Many traditional techniques use graph-based mechanisms, which reduce prediction accuracy and introduce large amounts of noise. The other problem...
Persistent link: https://www.econbiz.de/10015342727
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Measuring land lot shapes for property valuation
Lee, Changro - In: Data Technologies and Applications 58 (2023) 2, pp. 267-279
Purpose Unstructured data such as images have defied usage in property valuation for a long time. Instead, structured data in tabular format are commonly employed to estimate property prices. This study attempts to quantify the shape of land lots and uses the resultant output as an input...
Persistent link: https://www.econbiz.de/10015342733
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Entity deduplication in big data graphs for scholarly communication
Manghi, Paolo; Atzori, Claudio; De Bonis, Michele; … - In: Data Technologies and Applications 54 (2020) 4, pp. 409-435
Purpose Several online services offer functionalities to access information from “big research graphs” (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects,...
Persistent link: https://www.econbiz.de/10014712747
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Social recruiting: an application of social network analysis for preselection of candidates
Milovanović, Stevan; Bogdanović, Zorica; Labus, Aleksandra - In: Data Technologies and Applications 56 (2022) 4, pp. 536-557
Purpose The paper aims to studiy social recruiting for finding suitable candidates on social networks. The main goal is to develop a methodological approach that would enable preselection of candidates using social network analysis. The research focus is on the automated collection of data using...
Persistent link: https://www.econbiz.de/10014712609
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SeaRank: relevance prediction based on click models in a reinforcement learning framework
Keyhanipour, Amir Hosein; Oroumchian, Farhad - In: Data Technologies and Applications 57 (2022) 4, pp. 465-488
Purpose User feedback inferred from the user's search-time behavior could improve the learning to rank (L2R) algorithms. Click models (CMs) present probabilistic frameworks for describing and predicting the user's clicks during search sessions. Most of these CMs are based on common assumptions...
Persistent link: https://www.econbiz.de/10014712611
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Hybrid data analytic technique for grading fairness
Banditwattanawong, Thepparit; Jankasem, Arnon Marco Polo; … - In: Data Technologies and Applications 57 (2022) 1, pp. 18-31
Purpose Fair grading produces learning ability levels that are understandable and acceptable to both learners and instructors. Norm-referenced grading can be achieved by several means such as z score, K -means and a heuristic. However, these methods typically deliver the varied degrees of...
Persistent link: https://www.econbiz.de/10014712612
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A hybrid approach for predicting missing follower–followee links in social networks using topological features with ensemble learning
Bhattacharya, Riju; Nagwani, Naresh Kumar; Tripathi, Sarsij - In: Data Technologies and Applications 57 (2022) 1, pp. 131-153
Purpose Social networking platforms are increasingly using the Follower Link Prediction tool in an effort to expand the number of their users. It facilitates the discovery of previously unidentified individuals and can be employed to determine the relationships among the nodes in a social...
Persistent link: https://www.econbiz.de/10014712628
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A cascaded deep-learning-based model for face mask detection
Kumar, Akhil - In: Data Technologies and Applications 57 (2022) 1, pp. 84-107
Purpose This work aims to present a deep learning model for face mask detection in surveillance environments such as automatic teller machines (ATMs), banks, etc. to identify persons wearing face masks. In surveillance environments, complete visibility of the face area is a guideline, and...
Persistent link: https://www.econbiz.de/10014712629
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Privacy-preserving techniques in recommender systems: state-of-the-art review and future research agenda
Pramod, Dhanya - In: Data Technologies and Applications 57 (2022) 1, pp. 32-55
Purpose This study explores privacy challenges in recommender systems (RSs) and how they have leveraged privacy-preserving technology for risk mitigation. The study also elucidates the extent of adopting privacy-preserving RSs and postulates the future direction of research in RS security....
Persistent link: https://www.econbiz.de/10014712630
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Research on the generalization of social bot detection from two dimensions: feature extraction and detection approaches
Zeng, Ziming; Li, Tingting; Sun, Jingjing; Sun, Shouqiang; … - In: Data Technologies and Applications 57 (2022) 2, pp. 177-198
Purpose The proliferation of bots in social networks has profoundly affected the interactions of legitimate users. Detecting and rejecting these unwelcome bots has become part of the collective Internet agenda. Unfortunately, as bot creators use more sophisticated approaches to avoid being...
Persistent link: https://www.econbiz.de/10014712631
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