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Identifying Popular Search Goals behind Search Queries to Improve Web Search Ranking

机译:识别搜索查询背后的流行搜索目标,以改善Web搜索排名

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Web users usually have a certain search goal before they submit a search query. However, many laypersons can't transform their search goals into suitable queries. Thus, understanding original search goals behind a query is very important for search engines. In the past decade, many researches focus on classifying search goals behind a query into different search-goal categories. In fact, there may be more than one search goal behind a certain query. We thus propose a novel Popular-Search-Goal-based Search Model to effectively identify search goals by the features extracted from search-result snippets and click-through data. Furthermore, we proposed a Search-Goal-based Ranking Model which exploits the identified search goals to re-rank the search result. The experimental result shows our proposed model can effectively identify the search goals behind a search query (achieve precision of 0.94) and enhance the search result ranking (achieve precision of 0.72 for top- returned snippet).
机译:在提交搜索查询之前,Web用户通常具有某个搜索目标。但是,许多PATPERSONS无法将其搜索目标转换为合适的查询。因此,了解查询后面的原始搜索目标对于搜索引擎非常重要。在过去十年中,许多研究侧重于将查询后面的搜索目标分类为不同的搜索目标类别。实际上,某些查询后面可能有多个搜索目标。因此,我们提出了一种基于新的流行搜索目标的搜索模型,以通过从搜索结果片段和点击数据中提取的功能有效地识别搜索目标。此外,我们提出了一种基于搜索目标的排名模型,它利用所识别的搜索目标来重新排名搜索结果。实验结果表明我们所提出的模型可以有效地识别搜索查询背后的搜索目标(实现0.94的精度),并增强搜索结果排名(为顶部返回的片段实现0.72的精度)。

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