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Human or Automatic Answers? A User's Based Study

机译:人类或自动答案?用户的基于学习

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Understanding the different ways of the information seeking behavior of users, and their implications is an important challenge of Web Information Services. In this paper we examine the suitability of Web Search Engines (SE)and Community Question-Answering (community QA) to satisfy the different expectations of users: queries expecting knowledge-based answers, and queries expecting subjective opinion-based answers. From this categorization, we conducted a user study of the results obtained from three Web SE, and three Communities QA. In this way, we found that SE result in a better alternative when the query is designed to get a uni-objective answer, while communities QA provide better results if the question gets multi-objective answers. On the other hand, when the query expects a subjective answer, none of these systems provides a very effective answer that can fulfill the expectations from the user. Knowing more about the type of queries that require human support would be useful to improve the user search experience in SE.
机译:了解寻求用户行为的不同方式,其含义是Web信息服务的重要挑战。在本文中,我们研究了Web搜索引擎(SE)和社区问题回答(社区QA)的适用性,以满足用户的不同期望:期望基于知识的答案的查询,以及期望基于主观意见的答案的查询。从该分类中,我们进行了从三个Web SE获得的结果的用户研究,以及三个社区QA。通过这种方式,我们发现当查询旨在获得Uni-Tome答案时,SE导致更好的替代方案,而社区QA提供更好的结果,如果问题获得多目标答案,则提供更好的结果。另一方面,查询期望主观答案,这些系统都没有提供非常有效的答案,可以满足用户的期望。了解有关要求人类支持的查询类型可用于改善SE中的用户搜索体验是有用的。

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