ITR: TeraScale Retrieval

ITR：TeraScale 检索

• 批准号: 0082655
• 负责人: Gregory Newby
• 金额: $ 44.85万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0082655&HistoricalAwards=false
• 关键词: ITR; TeraScale; Retrieval

ITR-0082655Newby, Gregory B.School of Information and Library Science, Universityof North Carolina at Chapel HillITR/SW: TeraScale RetrievalTeraScale Retrieval addresses the scientific investigation oflarge-scale information retrieval (IR). TeraScale Retrieval willfacilitate experimentation to advance knowledge of informationretrieval, especially text retrieval, by implementing a softwaretoolkit for IR research and development. IR systems seek to identifydocuments or passages from documents that satisfy a human informationneed. Text retrieval is directed at collections of relativelyunstructured documents, such as HTML documents, as well as morestructured documents (e.g., XML). In order to advance scientificknowledge and improve performance of IR, there is a need for asoftware toolkit that enables rapid and practical implementation ofexperimental IR systems. The TeraScale Retrieval toolkit willemphasize large-scale performance with terascale datasets: hundreds ofmillions of documents with terabytes of raw data, millions of uniqueterms, multiple languages, and potential for quadrillions (petascale)of sub-documents or document fragments. The toolkit will emphasizesoftware reuse, high-performance algorithms, and modularity for rapidprototyping and evaluation. Rather than moving quickly from academicuse to commercialization, TeraScale Retrieval will focus onexperimentation and evaluation to contribute to scientific knowledgeabout information seeking and use.

ITR-0082655 Newby，Gregory B.信息与图书馆科学学院，北卡罗来纳州教堂山分校ITR/SW：TeraScale RetrievalTeraScale Retrieval致力于大规模信息检索（IR）的科学研究。 TeraScale Retrieval将通过实现IR研究和开发的软件工具包，促进信息检索，特别是文本检索知识的实验。 IR系统寻求从满足人类信息需求的文档中识别文档或段落。 文本检索针对相对非结构化文档的集合，例如HTML文档，以及结构化程度更高的文档（例如，XML）。 为了推进科学知识和提高性能的IR，有一个软件工具包，使实验IR系统的快速和实用的实施需要。 TeraScale Retrieval工具包将强调对Terascale数据集的大规模性能：数亿个文档，原始数据为TB级，数百万个唯一术语，多种语言，以及潜在的千万亿（petascale）子文档或文档片段。 该工具包将强调软件重用、高性能算法和快速原型设计和评估的模块化。 TeraScale Retrieval并没有迅速从学术应用转向商业化，而是将重点放在实验和评估上，以促进有关信息搜索和使用的科学知识。