Results 61 to 70 of about 592,124 (303)
A review of associative classification mining [PDF]
, 2007 Associative classification mining is a promising approach in data mining that utilizes the association rule discovery techniques to construct classification systems, also known as associative classifiers.
Fadi Abdeljaber Thabtah, Thabtah, Fadi
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Text Clustering as Classification with Llms
Proceedings of the 2025 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region11 pages, 3 ...
Chen Huang 0007, Guoxiu He
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Molecular Oncology, EarlyView.The novel styrylquinazolinone‐based molecule W1B effectively suppresses glioblastoma by inhibiting IGF1R and EGFR. In high‐glucose microenvironments driving tumor resistance, W1B acts synergistically with the EGFR inhibitor dacomitinib. This combination safely blocks compensatory survival signaling in zebrafish xenograft models. Showcasing promising in
Patryk Rurka +9 more
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Benefits of associative classification within text categorisation [PDF]
, 2008 Associative Classification has been successfully employed in many diverse classification problem domains, showing high classification accuracy and adequate computation time relative to the other traditionally used solutions.
Osborne, Hugh +2 more
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Research on the internal influence factors of the text multi-classification problem
MATEC Web of Conferences, 2018 This paper mainly deals with the classification of text type data. The statistics show that more than 8000 articles have been reached in all kinds of documents retrieved by the optical network. However, there are few papers on the factors that affect the
Mingqiang Wu, Chang Furong, Zhang Kui
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Molecular Oncology, EarlyView.Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller +10 more
wiley +1 more source
A novel two stage scheme utilizing the test set for model selection in text classification [PDF]
, 2005 Text classification is a natural application domain for semi-supervised learning, as labeling documents is expensive, but on the other hand usually an abundance of unlabeled documents is available.
Pfahringer, Bernhard +2 more
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Six-Granularity Based Chinese Short Text Classification
IEEE Access, 2023 Short text classification is an important task in Natural Language Processing (NLP). The classification result for Chinese short text is always not ideal due to the sparsity problem of them.
Xinjie Sun, Zhifang Liu, Xingying Huo
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FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
Unsupervised multi-label text classification using a world knowledge ontology [PDF]
, 2012 The development of text classification techniques has been largely promoted in the past decade due to the increasing availability and widespread use of digital documents. Usually, the performance of text classification relies on the quality of categories
Hua Wang +8 more
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