Query segmentation revisited
Query segmentation revisited
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DOI：
10.1145/1963405.1963423
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发表时间：
2011-03
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通讯作者：
Matthias Hagen;Martin Potthast;Benno Stein;Christof Bräutigam
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作者：
Matthias Hagen;Martin Potthast;Benno Stein;Christof Bräutigam
我们解决查询分割的问题：给定一个关键字查询，任务是将关键字分组为短语，如果可能的话。以前的方法的问题实现合理的分割性能，但只对一个小语料库的手动分割查询进行测试。此外，许多以前的方法是相当复杂的，因为它们使用昂贵的功能，很难重新实现。本文的主要贡献是一种新的方法，查询分割，易于实现，快速，并配备了分割精度相媲美，目前国家的最先进的技术。我们的方法只使用原始网络n-gram频率和存储在哈希表中的维基百科标题。同时，我们引入了一个新的评价语料库的查询分割。它有大约50，000个人工注释的查询，比目前使用的语料库大两个数量级。
We address the problem of query segmentation: given a keyword query, the task is to group the keywords into phrases, if possible. Previous approaches to the problem achieve reasonable segmentation performance but are tested only against a small corpus of manually segmented queries. In addition, many of the previous approaches are fairly intricate as they use expensive features and are difficult to be reimplemented. The main contribution of this paper is a new method for query segmentation that is easy to implement, fast, and that comes with a segmentation accuracy comparable to current state-of-the-art techniques. Our method uses only raw web n-gram frequencies and Wikipedia titles that are stored in a hash table. At the same time, we introduce a new evaluation corpus for query segmentation. With about 50,000 human-annotated queries, it is two orders of magnitude larger than the corpus being used up to now.