{"@type": "dcat:Dataset", "accessLevel": "public", "accrualPeriodicity": "irregular", "bureauCode": ["026:00"], "contactPoint": {"@type": "vcard:Contact", "fn": "Elizabeth Foughty", "hasEmail": "mailto:elizabeth.a.foughty@nasa.gov"}, "description": "KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS\r\n\r\nBOLIN DING*, YINTAO YU*, BO ZHAO*, CINDY XIDE LIN*, JIAWEI HAN*, AND CHENGXIANG ZHAI*\r\n\r\nAbstract. We study the problem of keyword search in a data cube with text-rich dimension(s)\r\n(so-called text cube). The text cube is built on a multidimensional text database, where each row\r\nis associated with some text data (e.g., a document) and other structural dimensions (attributes).\r\nA cell in the text cube aggregates a set of documents with matching attribute values in a subset\r\nof dimensions. A cell document is the concatenation of all documents in a cell. Given a keyword\r\nquery, our goal is to find the top-k most relevant cells (ranked according to the relevance scores of\r\ncell documents w.r.t. the given query) in the text cube.\r\nWe define a keyword-based query language and apply IR-style relevance model for scoring and\r\nranking cell documents in the text cube. We propose two efficient approaches to find the top-k\r\nanswers. The proposed approaches support a general class of IR-style relevance scoring formulas\r\nthat satisfy certain basic and common properties. One of them uses more time for pre-processing\r\nand less time for answering online queries; and the other one is more efficient in pre-processing and\r\nconsumes more time for online queries. Experimental studies on the ASRS dataset are conducted\r\nto verify the efficiency and effectiveness of the proposed approaches.", "distribution": [{"@type": "dcat:Distribution", "description": "KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS", "downloadURL": "https://c3.nasa.gov/dashlink/static/media/publication/Paper_12_.pdf", "format": "PDF", "mediaType": "application/pdf", "title": "Paper 12 .pdf"}], "identifier": "DASHLINK_234", "issued": "2010-10-13", "keyword": ["ames", "dashlink", "nasa"], "landingPage": "https://c3.nasa.gov/dashlink/resources/234/", "modified": "2025-04-01", "programCode": ["026:029"], "publisher": {"@type": "org:Organization", "name": "Dashlink"}, "title": "KEYWORD SEARCH IN TEXT CUBE: FINDING TOP-K RELEVANT CELLS"}