上流社会
发表于 2025-3-26 23:28:28
Math and Computer Programming Languages,allel clustering of large textual data through Spark framework and implementing a new document hashing strategy. Experiments performed on several large collections of documents have shown the effectiveness of the proposed method compared to existing ones in terms of running time and clustering accuracy.
异端
发表于 2025-3-27 03:53:15
https://doi.org/10.1007/978-1-4842-2349-9is paper highlights the relevance of pre-training the CamemBERT model on a French financial dataset to extend its domain-specific vocabulary and fine-tuning it on extractive summarisation. We then evaluate the impact of textual data augmentation, improving the performance of our extractive text summarisation model by up to 6%–11%.
初学者
发表于 2025-3-27 07:37:49
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Aggregate
发表于 2025-3-27 11:45:49
Linux Distro Selection Criteriais data model. In this paper, we however argue that by concentrating on transaction related functionalities rather than analytical operations, most of these systems address the wrong data market. We motivate this claim by presenting several concrete arguments.
subordinate
发表于 2025-3-27 14:21:57
RDF Data Management is an Analytical Market, not a Transaction Oneis data model. In this paper, we however argue that by concentrating on transaction related functionalities rather than analytical operations, most of these systems address the wrong data market. We motivate this claim by presenting several concrete arguments.
arrogant
发表于 2025-3-27 20:31:45
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分离
发表于 2025-3-28 01:18:31
https://doi.org/10.1007/978-1-4842-5410-3annot fit in the main memory. Our function is developed in C++, but it can be easily called in Python. Experimental comparison with state-of-art Python packages show that our C++ function has comparative performance for both small and large graphs.
Obloquy
发表于 2025-3-28 05:50:30
A Chain Composite Item Recommender for Lifelong Pathwaysr measuring the quality of the recommended pathways. We experiment with both artificial and real datasets, showing our approach is a promising building block of an interactive lifelong pathways recommender system.
Decline
发表于 2025-3-28 10:12:52
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agenda
发表于 2025-3-28 11:54:44
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