{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["026:00"], "contactPoint": {"@type": "vcard:Contact", "fn": "Ashok Srivastava", "hasEmail": "mailto:ashok.n.srivastava@gmail.com"}, "description": "Sparse machine learning has recently \r\nemerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational cost. This paper posits that these methods can be extremely useful for understanding large collections of text documents, without requiring user expertise in machine learning. Our approach relies on three main ingredients: (a) multi-document text summarization and (b) comparative summarization of two corpora, both using \r\nparse regression or classifi\fcation; (c) sparse principal components and sparse graphical models for unsupervised analysis and visualization of large text \r\ncorpora. We validate our approach using a corpus of Aviation Safety Reporting System (ASRS) reports and demonstrate that the methods can reveal causal and contributing factors in runway incursions. Furthermore, we show that the methods automatically discover four main tasks that pilots perform during \r\nflight, which can aid in further understanding the causal and contributing factors to runway incursions and other drivers for aviation safety incidents. \r\n\r\nCitation:  L. El Ghaoui, G. C. Li, V. Duong, V. Pham, A. N. Srivastava, and K. Bhaduri, \u201cSparse Machine Learning Methods for Understanding Large Text Corpora,\u201d Proceedings of the Conference on Intelligent Data Understanding, 2011.", "distribution": [{"@type": "dcat:Distribution", "description": "cidu2011-dashlink.pdf", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/cidu2011-dashlink.pdf", "format": "PDF", "mediaType": "application/pdf", "title": "cidu2011-dashlink.pdf"}], "identifier": "DASHLINK_513", "issued": "2012-01-27", "keyword": ["ames", "dashlink", "nasa"], "landingPage": "https://c3.nasa.gov/dashlink/resources/513/", "modified": "2025-03-31", "programCode": ["026:029"], "publisher": {"@type": "org:Organization", "name": "Dashlink"}, "title": "Sparse Machine Learning Methods for Understanding Large Text Corpora"}