• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>User modeling and user-adapted interaction >Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine
【24h】

Exploiting Query Repetition and Regularity in an Adaptive Community-Based Web Search Engine

机译：在基于社区的自适应Web搜索引擎中利用查询重复性和规则性

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Search engines continue to struggle with the challenges presented by Web search: vague queries, impatient users and an enormous and rapidly expanding collection of unmo-derated, heterogeneous documents all make for an extremely hostile search environment. In this paper we argue that conventional approaches to Web search - those that adopt a traditional, document-centric, information retrieval perspective - are limited by their refusal to consider the past search behaviour of users during future search sessions. In particular, we argue that in many circumstances the search behaviour of users is repetitive and regular; the same sort of queries tend to recur and the same type of results are often selected. We describe how this observation can lead to a novel approach to a more adaptive form of search, one that leverages past search behaviours as a means to re-rank future search results in a way that recognises the implicit preferences of communities of searchers. We describe and evaluate the I-SPY search engine, which implements this approach to collaborative, community-based search. We show that it offers potential improvements in search performance, especially in certain situations where communities of searchers share similar information needs and use similar queries to express these needs. We also show that I-SPY benefits from important advantages when it comes to user privacy. In short, we argue that I-SPY strikes a useful balance between search personalization and user privacy, by offering a unique form of anonymous personalization, and in doing so may very well provide privacy-conscious Web users with an acceptable approach to personalized search.
机译：搜索引擎继续面对Web搜索带来的挑战：模糊的查询，急躁的用户以及庞大且迅速扩展的无人为数的异类文档集合，所有这些都构成了极其敌对的搜索环境。在本文中，我们认为，传统的Web搜索方法-采用传统的，以文档为中心的信息检索观点的方法-受到拒绝在将来的搜索会话中考虑用户过去的搜索行为的限制。特别是，我们认为，在许多情况下，用户的搜索行为是重复且有规律的。往往会出现相同类型的查询，并且通常会选择相同类型的结果。我们描述了这种观察如何可以导致一种新颖的方法，以一种更具适应性的搜索形式，该方法利用过去的搜索行为作为一种对未来搜索结果进行重新排名的方法，从而可以识别搜索者社区的隐性偏好。我们描述并评估了I-SPY搜索引擎，该引擎将这种方法实现为基于社区的协作搜索。我们表明，它可以提高搜索性能，特别是在某些情况下，搜索者社区共享相似的信息需求并使用相似的查询来表达这些需求。我们还表明，在用户隐私方面，I-SPY受益于重要优势。简而言之，我们认为I-SPY通过提供独特形式的匿名个性化在搜索个性化和用户隐私之间取得了有用的平衡，并且这样做可以很好地为注重隐私的Web用户提供可接受的个性化搜索方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号