GETTING CLOSER TO THE THINGS WE ARE LOOKING FOR - A PROPOSAL FOR ASPECT-DRIVEN TEXT ANALYSIS

Kurt Englmeier, M. Schneider
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Abstract

Locating facts in texts is still a challenge for retrieval systems. Instead of measuring the relevance of the entire text for a search query, the focus of our approach of fact retrieval and text mining is on spotting only essential parts of text. We propose to enrich search queries by aspects supporting highly precise retrieval. An aspect denotes the unique interpretation of a set of words that appear in close proximity. We conceive an aspect representation as a hierarchical structure composed by its semantic elements that, in turn, constitute the aspect’s implicit meaning. In this paper, we present the definition and application of aspect blueprints that serve as standardized representations of aspects. Our prototypical system Contexter operates on these blueprints and locates facts in texts. In a semi-automatic way, the system tries to detect variants of blueprints that the user can confirm or reject. Here, we illustrate our approach and system in the realm of economic information.
越来越接近我们正在寻找的东西-方面驱动的文本分析的建议
在文本中定位事实对检索系统来说仍然是一个挑战。我们的事实检索和文本挖掘方法的重点是发现文本的关键部分,而不是测量搜索查询的整个文本的相关性。我们建议通过支持高度精确检索的方面来丰富搜索查询。一个方面表示对一组词语的唯一解释,这些词语出现得很近。我们将方面表示视为由其语义元素组成的层次结构,而语义元素又构成了方面的隐含意义。在本文中,我们提出了作为方面的标准化表示的方面蓝图的定义和应用。我们的原型系统Contexter在这些蓝图上运行,并在文本中定位事实。以半自动的方式,系统尝试检测用户可以确认或拒绝的蓝图变体。在这里,我们将说明我们在经济信息领域的方法和系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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