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Titlebook: Natural Language Information Retrieval; Tomek Strzalkowski Book 1999 Springer Science+Business Media Dordrecht 1999 DOM.Syntax.classificat

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21#
發(fā)表于 2025-3-25 05:39:46 | 只看該作者
Evaluating Natural Language Processing Techniques in Information Retrieval,ion retrieval, but the empirical evidence to support such predictions has thus far been inadequate, and appropriate scale evaluations have been slow to emerge. In this chapter, we report on the progress of the Natural Language Information Retrieval project, a joint effort of several sites led by GE
22#
發(fā)表于 2025-3-25 08:36:59 | 只看該作者
23#
發(fā)表于 2025-3-25 11:48:21 | 只看該作者
LaSIE Jumps the GATE,MUC evaluations, have been enormous, but it must now be time to ask what research issues face the systems we have built and what we should do next. We suggest that there are two classes of important research issues: those requiring detailed comparative evaluation of alternative approaches to IE subt
24#
發(fā)表于 2025-3-25 17:51:05 | 只看該作者
Phrasal Terms in Real-World IR Applications,asal terms. One large-scale empirical study has provided supporting evidence that phrasal terms can improve retrieval effectiveness, especially when their relative proximity information is understood from the naturally running text. To automatically identify significant terms for a predefined topic,
25#
發(fā)表于 2025-3-25 21:24:14 | 只看該作者
Name Recognition and Retrieval Performance,ation retrieval through name recognition. It investigates name recognition accuracy, and the effect on retrieval performance of indexing and searching personal names differently from non-name terms in the context of ranked retrieval. The main conclusions are: that name recognition in text can be eff
26#
發(fā)表于 2025-3-26 01:38:20 | 只看該作者
COLLAGE: An NLP Toolset to Support Boolean Retrieval,sed to determine which NLP resources should be applied to converting each part of a topic into a set of Boolean queries, and how the document lists resulting from the application of each query should be combined to give a final list of ranked documents.
27#
發(fā)表于 2025-3-26 07:38:17 | 只看該作者
28#
發(fā)表于 2025-3-26 08:55:09 | 只看該作者
29#
發(fā)表于 2025-3-26 13:10:43 | 只看該作者
The Use of Categories and Clusters for Organizing Retrieval Results,t categorization and text clustering are two natural language processing tasks whose results can be applied to document organization. This chapter describes user interfaces that use categories and clusters to organize retrieval results, and examines the relationship between the two..
30#
發(fā)表于 2025-3-26 19:21:07 | 只看該作者
Text, Speech and Language Technologyhttp://image.papertrans.cn/n/image/661791.jpg
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