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Posts

ArabicNLP Dataset

less than 1 minute read

Published:

A list of resources for Arabic NLP.

Heuristics: the art of good guessing

10 minute read

Published:

Heuristics explained with a simple numeric minimization problem using Particle swarm optimization technique.

portfolio

publications

Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media

Published in ASONAM '17 Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, 2017

Recommended citation: Amir Hossein Yazdavar, Hussein S. Al-Olimat, Monireh Ebrahimi, Goonmeet Bajaj, Tanvi Banerjee, Krishnaprasad Thirunarayan, Jyotishman Pathak, and Amit Sheth. 2017. Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 (ASONAM '17), Jana Diesner, Elena Ferrari, and Guandong Xu (Eds.). ACM, New York, NY, USA, 1191-1198. https://dl.acm.org/citation.cfm?doid=3110025.3123028

Location Name Extraction from Targeted Text Streams using Gazetteer-based Statistical Language Models

Published in COLING 2018, 2018

Recommended citation: Hussein S. Al-Olimat, Krishnaprasad Thirunarayan, Valerie Shalin, and Amit Sheth. 2018. Location Name Extraction from Targeted Text Streams using Gazetteer-based Statistical Language Models. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018), pages 1986–1997. Association for Computational Linguistics. https://www.aclweb.org/anthology/papers/C/C18/C18-1169/

A Practical Incremental Learning Framework For Sparse Entity Extraction

Published in COLING 2018, 2018

Recommended citation: Hussein S. Al-Olimat, Steven Gustafson, Jason Mackay, Krishnaprasad Thirunarayan, and Amit Sheth. 2018. A practical incremental learning framework for sparse entity extraction. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018), pages 700–710. Association for Computational Linguistics. https://www.aclweb.org/anthology/papers/C/C18/C18-1059/

D-record: Disaster Response and Relief Coordination Pipeline

Published in ARIC'18 Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities, 2018

Recommended citation: Shruti Kar, Hussein S. Al-Olimat, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit Sheth, and Srinivasan Parthasarathy. 2018. D-record: Disaster Response and Relief Coordination Pipeline. In Proceedings of the 1st ACM SIGSPATIAL Workshop on Advances on Resilient and Intelligent Cities (ARIC'18), Bandana Kar, Olufemi A. Omitaomu, Shima Mohebbi, and Guangtao Fu (Eds.). ACM, New York, NY, USA, 13-16. DOI: https://doi.org/10.1145/3284566.3284572 https://dl.acm.org/citation.cfm?id=3284572

A Pipeline for Disaster Response and Relief Coordination

Published in SIGIR'19 Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019

Recommended citation: Maneriker, Pranav, Nikhita Vedula, Hussein S. Al-Olimat, Jiayong Liang, Omar El-Khoury, Ethan Kubatko, Desheng Liu et al. A Pipeline for Disaster Response and Relief Coordination. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1337-1340. ACM, 2019. https://dl.acm.org/citation.cfm?id=3331405

Towards Geocoding Spatial Expressions (Vision Paper)

Published in SIGSPATIAL 2019, 2019

Recommended citation: Hussein S. Al-Olimat, Valerie Shalin, Krishnaprasad Thirunarayan, and Joy Prakash Sain. 2019. Towards Geocoding Spatial Expressions (vision paper). In Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL '19). ACM, New York, NY, USA. DOI: https://doi.org/10.1145/3347146.3359356 https://arxiv.org/abs/1906.04960

Leveraging machine learning technology to efficiently identify and match patients for precision oncology clinical trials

Published in ASCO 2021, 2021

Recommended citation: Laura Sachse, Smriti Dasari, Marc Ackermann, Emily Patnaude, Stephanie OLeary, Hussein Al-Olimat, Alexander Grigorenko, Andrew Stewart, AnnaJane Ward, Annie Darmofal, Sowmya Ballakur, William Bennett, Amy Franzen, Sibel Blau, Abhinav Binod Chandra, Petros Nikolinakos, James Michael Orsini, Julio Antonio Peguero, Kimberly L. Blackwell, and Matthew M. Cooney. Leveraging machine learning technology to efficiently identify and match patients for precision oncology clinical trials. Journal of Clinical Oncology 2021 39:15_suppl, e13588-e13588 https://ascopubs.org/doi/abs/10.1200/JCO.2021.39.15_suppl.e13588

GazPNE Annotation-free Deep Learning for Place Name Extraction from Microblogs Leveraging Gazetteer and Synthetic Data by Rules

Published in International Journal of Geographical Information Science, 2021

Recommended citation: Hu, Xuke, Hussein S. Al-Olimat, Jens Kersten, Matti Wiegmann, Friederike Klan, Yeran Sun, and Hongchao Fan. GazPNE: annotation-free deep learning for place name extraction from microblogs leveraging gazetteer and synthetic data by rules. International Journal of Geographical Information Science 36, no. 2 (2022): 310-337. https://www.tandfonline.com/doi/abs/10.1080/13658816.2021.1947507?journalCode=tgis20

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