NLP
This dataset comprises a comprehensive collection of PubMed abstracts and associated metadata focusing on the topic of multiple sclerosis (MS) in relation to social determinants and environmental factors, spanning publications from January 1, 2018, to December 31, 2023. The data was meticulously gathered using the PubMed E-Utilities API with the search query "multiple sclerosis" AND ("social determinants" OR "environmental factors")
. Articles classified as preprints were excluded to ensure the inclusion of peer-reviewed research only.
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To download this dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13896353
Please cite the following paper when using this dataset:
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To download the dataset without purchasing an IEEE Dataport subscription, please visit: https://zenodo.org/records/13738598
Please cite the following paper when using this dataset:
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As shown in the figure 1, the NLP market is projected to grow from USD 31.76 billion in 2024 to USD 92.99 billion by 2029. This growth is driven by advances in deep learning and algorithms, increased digitization, and the integration of NLP with machine learning and deep learning. Key factors contributing to this expansion include the increasing use of NLP in healthcare and call centers, the demand for advanced text analytics, and growing machine-to-machine technology.
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Microsoft contains a productive tool known as MS Office but the inclusion of VBA Macros inside the MS Office for automation purposes makes it a way for attackers to perform malicious activities. To get an up-to-date dataset, the research regarding VBA macros is still working to find efficient ways to detect it. To perform analysis, the dataset is required which is publically harder to find. To overcome this issue, a dataset is created from VirusTotal, VirusShare, Zenodo, Malware Bazaar, Github and InQuest Labs.
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We looked at 10,269 users on Twitter and collected their tweets and the follower network from April 2019 to October 2019. We organized tweets with the same hashtag into 29,192 cascades. To find an active community, we first selected 500 popular seed users. Subsequently, we added users who followed these seed users to the target group. After adding more users iteratively for five rounds, we locked the target group.
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The Narrative question answering (QA) problem involves generating accurate, relevant, and human-like answers to questions based on the comprehension of a story consisting of logically connected paragraphs. However, this problem remains unexplored for the Arabic language because of the lack of Arabic narrative datasets. To address this gap, we present the Arabic-NarrativeQA dataset, which is the first dataset specifically designed for machine-reading comprehension of Arabic stories.
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Mizo or Lushai language is the official language of Mizoram, a state in the north-eastern part of India. It is an under-resourced language that falls under the Tibeto-Burman language family and is highly tonal in nature.
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Mizo or Lushai language is the official language of Mizoram, a state in the north-eastern part of India. It is an under-resourced language that falls under the Tibeto-Burman language family and is highly tonal in nature.
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