Characterizing commercial intent

Azin Ashkan, C. Clarke
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引用次数: 21

Abstract

Understanding the intent underlying user's queries may help personalize search results and therefore improve user satisfaction. We develop a methodology for using the content of search engine result pages (SERPs) along with the information obtained from query strings to study characteristics of query intent, with a particular focus on sponsored search. This work represents an initial step towards the development and evaluation of an ontology for commercial search, considering queries that reference specific products, brands and retailers. The characteristics of query categories are studied with respect to aggregated user's clickthrough behavior on advertising links. We present a model for clickthrough behavior that considers the influence of such factors as the location of ads and the rank of ads, along with query category. We evaluate our work using a large corpus of clickthrough data obtained from a major commercial search engine. Our findings suggest that query based features, along with the content of SERPs, are effective in detecting query intent. The clickthrough behavior is found to be consistent with the classification for the general categories of query intent, while for product, brand and retailer categories, all is true to a lesser extent.
商业意图特征
了解用户查询背后的意图可能有助于个性化搜索结果,从而提高用户满意度。我们开发了一种方法,用于使用搜索引擎结果页面(serp)的内容以及从查询字符串中获得的信息来研究查询意图的特征,特别关注赞助搜索。这项工作代表了商业搜索本体开发和评估的第一步,考虑了参考特定产品、品牌和零售商的查询。针对聚合用户在广告链接上的点击行为,研究了查询类别的特征。我们提出了一个点击行为模型,该模型考虑了广告位置、广告排名以及查询类别等因素的影响。我们使用从主要商业搜索引擎获得的大量点击数据来评估我们的工作。我们的研究结果表明,基于查询的特征以及serp的内容在检测查询意图方面是有效的。发现点击行为与查询意图的一般类别的分类一致,而对于产品、品牌和零售商类别,都在较小程度上是正确的。
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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