NETSPEAK WORDGRAPH:可视化上下文中的关键字

P. Riehmann, Henning Gruendl, B. Fröhlich, Martin Potthast, Martin Trenkmann, Benno Stein
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引用次数: 10

摘要

NETSPEAK帮助作家在写作时选词。它检查短语的共性,并允许通过通配符查询检索备选项。为了支持这样的查询,我们实现了一个可伸缩的检索引擎,它使用概率检索策略在几毫秒内返回高质量的结果。结果显示为WORDGRAPH可视化或文本列表。图形界面为使用过滤技术、查询扩展和导航对搜索结果进行交互式探索提供了有效的手段。我们的观察表明,在三个被调查的检索任务中,文本界面足以满足短语验证任务,其中两个视图都支持上下文敏感的单词选择,WORDGRAPH最好地支持短语上下文或底层语料库的探索。上下文敏感的单词选择的首选视图似乎取决于查询的复杂性(即查询中的通配符数量)。
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The NETSPEAK WORDGRAPH: Visualizing keywords in context
NETSPEAK helps writers in choosing words while writing a text. It checks for the commonness of phrases and allows for the retrieval of alternatives by means of wildcard queries. To support such queries, we implement a scalable retrieval engine, which returns high-quality results within milliseconds using a probabilistic retrieval strategy. The results are displayed as WORDGRAPH visualization or as a textual list. The graphical interface provides an effective means for interactive exploration of search results using filter techniques, query expansion and navigation. Our observations indicate that, of three investigated retrieval tasks, the textual interface is sufficient for the phrase verification task, wherein both views support context-sensitive word choice, and the WORDGRAPH best supports the exploration of a phrase's context or the underlying corpus. The preferred view for context-sensitive word choice seems to depend on query complexity (i.e. the number of wildcards in a query).
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