信息检索中的再现性专题导论

N. Ferro, N. Fuhr, A. Rauber
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引用次数: 5

摘要

信息检索(Information Retrieval, IR)是一门从诞生之初就深深植根于实验的学科。实验评估一直是信息检索研究和创新的强大驱动力,这些活动受到大规模评估活动的影响,如美国的文本检索会议(TREC),欧洲的评估论坛会议和实验室(CLEF),日本和亚洲的NII测试平台和信息访问研究社区(NTCIR),以及印度的信息检索评估论坛(FIRE)。红外系统正变得越来越复杂。他们需要跨越语言和媒体障碍;从非结构化到半结构化,再到高度结构化的数据;他们还面临着各种各样的、复杂的、经常不明确的(不明确的)信息需求、搜索任务和社会挑战。因此,评价和实验,这仍然是一个基本因素,反过来也变得越来越复杂和具有挑战性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Introduction to the Special Issue on Reproducibility in Information Retrieval
Information Retrieval (IR) is a discipline that has been strongly rooted in experimentation since its inception. Experimental evaluation has always been a strong driver for IR research and innovation, and these activities have been shaped by large-scale evaluation campaigns such as Text REtrieval Conference (TREC) in the U.S., Conference and Labs of the Evaluation Forum (CLEF) in Europe, NII Testbeds and Community for Information access Research (NTCIR) in Japan and Asia, and Forum for Information Retrieval Evaluation (FIRE) in India. IR systems are getting increasingly complex. They need to cross language and media barriers; they span from unstructured, via semi-structured, to highly structured data; and they are faced with diverse, complex, and frequently underspecified (ambiguously specified) information needs, search tasks, and societal challenges. As a consequence, evaluation and experimentation, which has remained a fundamental element, has in turn become increasingly sophisticated and challenging.
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