让新手用英语轻松构建跨语言检索查询
QueryBuilder: Human-in-the-Loop Query Development for Information Retrieval
- 用户标记相关句子，系统据此优化查询词权重和语义
- 10分钟内完成子主题查询，支持不懂目标语言的用户
- 适合需要快速构建多语言检索需求的研究人员
信息检索系统中，用户常从宏观信息需求出发，逐步细化为覆盖多个子主题的具体查询。我们提出交互式系统 QueryBuilder，允许英语母语的新手用户通过高效探索英文语料库，在少量投入（每子主题最多10分钟）下快速构建跨语言信息检索查询。用户输入关键词后，系统实时返回文档，用户标记相关句子；这些标记用于动态调整查询词权重，并结合神经模型捕捉文本深层语义，进一步召回相关内容。该过程可重复迭代，持续优化查询。实验基于 IARPA BETTER IR 数据集中的分析任务，结果表明，即使不熟悉目标语言，用户也能生成有效细粒度查询。QueryBuilder 还提升了传统语料探索与查询构建效率。演示视频见 https://vimeo.com/734795835。
原文摘要 · Abstract (English)
Frequently, users of an Information Retrieval (IR) system start with an overarching information need (a.k.a., an analytic task) and proceed to define finer-grained queries covering various important aspects (i.e., sub-topics) of that analytic task. We present a novel, interactive system called $\textit{QueryBuilder}$, which allows a novice, English-speaking user to create queries with a small amount of effort, through efficient exploration of an English development corpus in order to rapidly develop cross-lingual information retrieval queries corresponding to the user's information needs. QueryBuilder performs near real-time retrieval of documents based on user-entered search terms; the user looks through the retrieved documents and marks sentences as relevant to the information needed. The marked sentences are used by the system as additional information in query formation and refinement: query terms (and, optionally, event features, which capture event $'triggers'$ (indicator terms) and agent/patient roles) are appropriately weighted, and a neural-based system, which better captures textual meaning, retrieves other relevant content. The process of retrieval and marking is repeated as many times as desired, giving rise to increasingly refined queries in each iteration. The final product is a fine-grained query used in Cross-Lingual Information Retrieval (CLIR). Our experiments using analytic tasks and requests from the IARPA BETTER IR datasets show that with a small amount of effort (at most 10 minutes per sub-topic), novice users can form $\textit{useful}$ fine-grained queries including in languages they don't understand. QueryBuilder also provides beneficial capabilities to the traditional corpus exploration and query formation process. A demonstration video is released at https://vimeo.com/734795835
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