[{"citation":{"ama":"Vollmers D, Jalota R, Moussallem D, Topiwala H, Ngonga Ngomo A-C, Usbeck R. Knowledge Graph Question Answering using Graph-Pattern Isomorphism. <i>CoRR</i>. 2021;abs/2103.06752.","ieee":"D. Vollmers, R. Jalota, D. Moussallem, H. Topiwala, A.-C. Ngonga Ngomo, and R. Usbeck, “Knowledge Graph Question Answering using Graph-Pattern Isomorphism,” <i>CoRR</i>, vol. abs/2103.06752, 2021.","chicago":"Vollmers, Daniel, Rricha Jalota, Diego Moussallem, Hardik Topiwala, Axel-Cyrille Ngonga Ngomo, and Ricardo Usbeck. “Knowledge Graph Question Answering Using Graph-Pattern Isomorphism.” <i>CoRR</i> abs/2103.06752 (2021).","apa":"Vollmers, D., Jalota, R., Moussallem, D., Topiwala, H., Ngonga Ngomo, A.-C., &#38; Usbeck, R. (2021). Knowledge Graph Question Answering using Graph-Pattern Isomorphism. <i>CoRR</i>, <i>abs/2103.06752</i>.","mla":"Vollmers, Daniel, et al. “Knowledge Graph Question Answering Using Graph-Pattern Isomorphism.” <i>CoRR</i>, vol. abs/2103.06752, 2021.","bibtex":"@article{Vollmers_Jalota_Moussallem_Topiwala_Ngonga Ngomo_Usbeck_2021, title={Knowledge Graph Question Answering using Graph-Pattern Isomorphism}, volume={abs/2103.06752}, journal={CoRR}, author={Vollmers, Daniel and Jalota, Rricha and Moussallem, Diego and Topiwala, Hardik and Ngonga Ngomo, Axel-Cyrille and Usbeck, Ricardo}, year={2021} }","short":"D. Vollmers, R. Jalota, D. Moussallem, H. Topiwala, A.-C. Ngonga Ngomo, R. Usbeck, CoRR abs/2103.06752 (2021)."},"year":"2021","date_created":"2021-10-01T06:51:45Z","author":[{"last_name":"Vollmers","full_name":"Vollmers, Daniel","first_name":"Daniel"},{"first_name":"Rricha","last_name":"Jalota","full_name":"Jalota, Rricha","id":"69526"},{"full_name":"Moussallem, Diego","id":"71635","last_name":"Moussallem","first_name":"Diego"},{"first_name":"Hardik","full_name":"Topiwala, Hardik","last_name":"Topiwala"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille"},{"first_name":"Ricardo","last_name":"Usbeck","full_name":"Usbeck, Ricardo"}],"volume":"abs/2103.06752","date_updated":"2022-01-06T06:56:55Z","title":"Knowledge Graph Question Answering using Graph-Pattern Isomorphism","type":"journal_article","publication":"CoRR","status":"public","user_id":"65716","department":[{"_id":"574"}],"_id":"25211","language":[{"iso":"eng"}]},{"citation":{"ama":"Zahera HMA, Jalota R, Sherif M, Ngonga Ngomo A-C. I-AID: Identifying Actionable Information from Disaster-related Tweets. In: <i>IEEE Open Access</i>. ; 2021.","ieee":"H. M. A. Zahera, R. Jalota, M. Sherif, and A.-C. Ngonga Ngomo, “I-AID: Identifying Actionable Information from Disaster-related Tweets,” 2021.","chicago":"Zahera, Hamada Mohamed Abdelsamee, Rricha Jalota, Mohamed Sherif, and Axel-Cyrille Ngonga Ngomo. “I-AID: Identifying Actionable Information from Disaster-Related Tweets.” In <i>IEEE Open Access</i>, 2021.","apa":"Zahera, H. M. A., Jalota, R., Sherif, M., &#38; Ngonga Ngomo, A.-C. (2021). I-AID: Identifying Actionable Information from Disaster-related Tweets. <i>IEEE Open Access</i>.","short":"H.M.A. Zahera, R. Jalota, M. Sherif, A.-C. Ngonga Ngomo, in: IEEE Open Access, 2021.","mla":"Zahera, Hamada Mohamed Abdelsamee, et al. “I-AID: Identifying Actionable Information from Disaster-Related Tweets.” <i>IEEE Open Access</i>, 2021.","bibtex":"@inproceedings{Zahera_Jalota_Sherif_Ngonga Ngomo_2021, title={I-AID: Identifying Actionable Information from Disaster-related Tweets}, booktitle={IEEE Open Access}, author={Zahera, Hamada Mohamed Abdelsamee and Jalota, Rricha and Sherif, Mohamed and Ngonga Ngomo, Axel-Cyrille}, year={2021} }"},"year":"2021","title":"I-AID: Identifying Actionable Information from Disaster-related Tweets","author":[{"orcid":"0000-0003-0215-1278","last_name":"Zahera","full_name":"Zahera, Hamada Mohamed Abdelsamee","id":"72768","first_name":"Hamada Mohamed Abdelsamee"},{"first_name":"Rricha","id":"69526","full_name":"Jalota, Rricha","last_name":"Jalota"},{"id":"67234","full_name":"Sherif, Mohamed","last_name":"Sherif","orcid":"https://orcid.org/0000-0002-9927-2203","first_name":"Mohamed"},{"last_name":"Ngonga Ngomo","id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","first_name":"Axel-Cyrille"}],"date_created":"2021-12-17T10:06:30Z","date_updated":"2023-08-16T09:35:42Z","status":"public","abstract":[{"lang":"eng","text":"Social media plays a significant role in disaster management by providing valuable data about affected people, donations and help requests. Recent studies highlight the need to filter information on social media into fine-grained content labels. However, identifying useful information from massive amounts of social media posts during a crisis is a challenging task. In this paper, we propose I-AID, a multimodel approach to automatically categorize tweets into multi-label information types and filter critical information from the enormous volume of social media data. I-AID incorporates three main components: i) a BERT- based encoder to capture the semantics of a tweet and represent as a low-dimensional vector, ii) a graph attention network (GAT) to apprehend correlations between tweets’ words/entities and the corresponding information types, and iii) a Relation Network as a learnable distance metric to compute the similarity between tweets and their corresponding information types in a supervised way. We conducted several experiments on two real publicly-available datasets. Our results indicate that I-AID outperforms state-of- the-art approaches in terms of weighted average F1 score by +6% and +4% on the TREC-IS dataset and COVID-19 Tweets, respectively."}],"type":"conference","publication":"IEEE Open Access","language":[{"iso":"eng"}],"keyword":["sys:relevantFor:infai sys:relevantFor:DAIKIRI ngonga zahera sherif daikiriproject dice simba"],"user_id":"67234","_id":"29043"},{"publication":"Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019","type":"conference","abstract":[{"text":"In this paper, we describe our approach to classify disaster-related tweets into multilabel information types (ie, labels). We aim to filter first relevant tweets during disasters. Then, we assign tweets relevant information types. Information types can be SearchAndRescue, MovePeople and Volunteer. We employ a fine-tuned BERT model with 10 BERT layers. Further, we submitted our approach to the TREC-IS 2019 challenge, the evaluation results showed that our approach outperforms the F1-score of median score in identifying actionable information.","lang":"eng"}],"status":"public","_id":"29003","user_id":"67234","keyword":["zahera elgendy jalota sherif dice"],"language":[{"iso":"eng"}],"year":"2019","citation":{"short":"H.M.A. Zahera, I. A. Elgendy, R. Jalota, M. Sherif, in: Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019, 2019.","bibtex":"@inproceedings{Zahera_A. Elgendy_Jalota_Sherif_2019, title={Fine-tuned BERT Model for Multi-Label Tweets Classification}, booktitle={Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019}, author={Zahera, Hamada Mohamed Abdelsamee and A. Elgendy, Ibrahim and Jalota, Rricha and Sherif, Mohamed}, year={2019} }","mla":"Zahera, Hamada Mohamed Abdelsamee, et al. “Fine-Tuned BERT Model for Multi-Label Tweets Classification.” <i>Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019</i>, 2019.","apa":"Zahera, H. M. A., A. Elgendy, I., Jalota, R., &#38; Sherif, M. (2019). Fine-tuned BERT Model for Multi-Label Tweets Classification. <i>Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019</i>.","chicago":"Zahera, Hamada Mohamed Abdelsamee, Ibrahim A. Elgendy, Rricha Jalota, and Mohamed Sherif. “Fine-Tuned BERT Model for Multi-Label Tweets Classification.” In <i>Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019</i>, 2019.","ieee":"H. M. A. Zahera, I. A. Elgendy, R. Jalota, and M. Sherif, “Fine-tuned BERT Model for Multi-Label Tweets Classification,” 2019.","ama":"Zahera HMA, A. Elgendy I, Jalota R, Sherif M. Fine-tuned BERT Model for Multi-Label Tweets Classification. In: <i>Proceedings of the Twenty-Eighth Text REtrieval Conference, {TREC} 2019, Gaithersburg, Maryland, USA, November 13-15, 2019</i>. ; 2019."},"date_updated":"2023-08-16T09:25:34Z","author":[{"id":"72768","full_name":"Zahera, Hamada Mohamed Abdelsamee","orcid":"0000-0003-0215-1278","last_name":"Zahera","first_name":"Hamada Mohamed Abdelsamee"},{"first_name":"Ibrahim","last_name":"A. Elgendy","full_name":"A. Elgendy, Ibrahim"},{"full_name":"Jalota, Rricha","id":"69526","last_name":"Jalota","first_name":"Rricha"},{"orcid":"https://orcid.org/0000-0002-9927-2203","last_name":"Sherif","full_name":"Sherif, Mohamed","id":"67234","first_name":"Mohamed"}],"date_created":"2021-12-17T09:48:17Z","title":"Fine-tuned BERT Model for Multi-Label Tweets Classification"},{"title":"Finding Datasets in Publications: The University of Paderborn Approach","date_created":"2024-11-20T10:44:54Z","author":[{"first_name":"Rricha","id":"69526","full_name":"Jalota, Rricha","last_name":"Jalota"},{"full_name":"Srivastava, Nikit","id":"70066","last_name":"Srivastava","orcid":"0009-0004-5164-4911","first_name":"Nikit"},{"first_name":"Daniel","full_name":"Vollmers, Daniel","last_name":"Vollmers"},{"first_name":"René","full_name":"Speck, René","id":"70843","last_name":"Speck"},{"id":"67199","full_name":"Röder, Michael","last_name":"Röder","orcid":"https://orcid.org/0000-0002-8609-8277","first_name":"Michael"},{"first_name":"Ricardo","full_name":"Usbeck, Ricardo","last_name":"Usbeck"},{"id":"65716","full_name":"Ngonga Ngomo, Axel-Cyrille","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille"}],"date_updated":"2024-11-20T10:53:14Z","publisher":"SAGE Publications","citation":{"chicago":"Jalota, Rricha, Nikit Srivastava, Daniel Vollmers, René Speck, Michael Röder, Ricardo Usbeck, and Axel-Cyrille Ngonga Ngomo. “Finding Datasets in Publications: The University of Paderborn Approach.” In <i>Rich Search and Discovery for Research Datasets</i>. SAGE Publications, 2019.","ieee":"R. Jalota <i>et al.</i>, “Finding Datasets in Publications: The University of Paderborn Approach,” in <i>Rich Search and Discovery for Research Datasets</i>, SAGE Publications, 2019.","ama":"Jalota R, Srivastava N, Vollmers D, et al. Finding Datasets in Publications: The University of Paderborn Approach. In: <i>Rich Search and Discovery for Research Datasets</i>. SAGE Publications; 2019.","apa":"Jalota, R., Srivastava, N., Vollmers, D., Speck, R., Röder, M., Usbeck, R., &#38; Ngonga Ngomo, A.-C. (2019). Finding Datasets in Publications: The University of Paderborn Approach. In <i>Rich Search and Discovery for Research Datasets</i>. SAGE Publications.","mla":"Jalota, Rricha, et al. “Finding Datasets in Publications: The University of Paderborn Approach.” <i>Rich Search and Discovery for Research Datasets</i>, SAGE Publications, 2019.","bibtex":"@inbook{Jalota_Srivastava_Vollmers_Speck_Röder_Usbeck_Ngonga Ngomo_2019, title={Finding Datasets in Publications: The University of Paderborn Approach}, booktitle={Rich Search and Discovery for Research Datasets}, publisher={SAGE Publications}, author={Jalota, Rricha and Srivastava, Nikit and Vollmers, Daniel and Speck, René and Röder, Michael and Usbeck, Ricardo and Ngonga Ngomo, Axel-Cyrille}, year={2019} }","short":"R. Jalota, N. Srivastava, D. Vollmers, R. Speck, M. Röder, R. Usbeck, A.-C. Ngonga Ngomo, in: Rich Search and Discovery for Research Datasets, SAGE Publications, 2019."},"year":"2019","language":[{"iso":"eng"}],"keyword":["dice jalota ngonga roeder speck srivastava vollmers"],"user_id":"70066","_id":"57286","status":"public","type":"book_chapter","publication":"Rich Search and Discovery for Research Datasets"}]