Document structure-driven investigative information retrieval

IF 3 2区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Information Systems Pub Date : 2023-11-19 DOI:10.1016/j.is.2023.102315
Tuomas Ketola, Thomas Roelleke
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引用次数: 0

Abstract

Data-driven investigations are increasingly dealing with non-moderated, non-standard and even manipulated information Whether the field in question is journalism, law enforcement, or insurance fraud it is becoming more and more difficult for investigators to verify the outcomes of various black-box systems To contribute to this need of discovery methods that can be used for verification, we introduce a methodology for document structure-driven investigative information retrieval (InvIR) InvIR is defined as a subtask of exploratory IR, where transparency and reasoning take centre stage The aim of InvIR is to facilitate the verification and discovery of facts from data and the communication of those facts to others From a technical perspective, the methodology applies recent work from structured document retrieval (SDR) concerned with formal retrieval constraints and information content-based field weighting (ICFW) Using ICFW, the paper establishes the concept of relevance structures to describe the document structure-based relevance of documents These contexts are then used to help the user navigate during their discovery process and to rank entities of interest The proposed methodology is evaluated using a prototype search system called Relevance Structure-based Entity Ranker (RSER) in order to demonstrate its the feasibility This methodology represents an interesting and important research direction in a world where transparency is becoming more vital than ever.

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文档结构驱动的调查信息检索
数据驱动的调查越来越多地处理未经审核的、非标准的甚至是被操纵的信息,无论所涉及的领域是新闻、执法还是保险欺诈,调查人员越来越难以验证各种黑匣子系统的结果。我们介绍了一种文档结构驱动的调查性信息检索(InvIR)方法。InvIR被定义为探索性信息检索的一个子任务,其中透明度和推理占据中心位置。InvIR的目的是促进从数据中验证和发现事实,并将这些事实与他人交流。该方法应用了结构化文档检索(SDR)中有关正式检索约束和基于信息内容的字段加权(ICFW)的最新工作。本文建立了相关结构的概念来描述基于文档结构的文档相关性,然后使用这些上下文来帮助用户在发现过程中导航并对感兴趣的实体进行排名。为了证明其可行性,使用基于关联结构的实体排名(RSER)原型搜索系统对所提出的方法进行了评估,该方法代表了一个有趣且重要的研究方向透明度变得比以往任何时候都更加重要。
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来源期刊
Information Systems
Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
2.70%
发文量
112
审稿时长
53 days
期刊介绍: Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems. Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.
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