Visual query suggestion
Visual query suggestion
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DOI：
10.1145/1631272.1631278
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
Zhengjun Zha;Linjun Yang;Tao Mei;Meng Wang;Zengfu Wang
中科院分区：
文献类型：
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作者：
Zhengjun Zha;Linjun Yang;Tao Mei;Meng Wang;Zengfu Wang
查询建议是提高图像搜索可用性的有效途径。大多数现有的搜索引擎都能够根据用户当前的查询输入自动建议一系列文本查询词，这可以称为文本查询建议。本文提出了一种新的查询建议方案可视化查询建议（VQS），专门用于图像搜索。它提供了一个更有效的查询接口，以制定一个意图特定的查询联合文本和图像的建议。我们表明，VQS能够更准确，更快速地帮助用户指定和提供他们的搜索意图。当用户提交一个文本查询时，VQS首先提供一个建议列表，每个建议包含一个关键字和一个菜单中的代表性图像集合。如果用户选择其中一个建议，则将添加相应的关键字以补充初始文本查询作为新的文本查询，而图像集合将被公式化为视觉查询。然后，VQS使用文本搜索技术基于新的文本查询执行图像搜索，以及基于内容的视觉检索，以通过使用相应的图像作为查询示例来细化搜索结果。我们比较VQS与三个流行的图像搜索引擎，并表明VQS优于这些引擎的查询建议和搜索性能的质量。
Query suggestion is an effective approach to improve the usability of image search. Most existing search engines are able to automatically suggest a list of textual query terms based on users' current query input, which can be called Textual Query Suggestion. This paper proposes a new query suggestion scheme named Visual Query Suggestion (VQS) which is dedicated to image search. It provides a more effective query interface to formulate an intent-specific query by joint text and image suggestions. We show that VQS is able to more precisely and more quickly help users specify and deliver their search intents. When a user submits a text query, VQS first provides a list of suggestions, each containing a keyword and a collection of representative images in a dropdown menu. If the user selects one of the suggestions, the corresponding keyword will be added to complement the initial text query as the new text query, while the image collection will be formulated as the visual query. VQS then performs image search based on the new text query using text search techniques, as well as content-based visual retrieval to refine the search results by using the corresponding images as query examples. We compare VQS with three popular image search engines, and show that VQS outperforms these engines in terms of both the quality of query suggestion and search performance.