改进实体消歧系统，支持局部合并与更优解选择。
Advances in Logic-Based Entity Resolution: Enhancing ASPEN with Local Merges and Optimality Criteria
- 引入局部合并机制，按场景区分相同名称的不同实体
- 提出最小化规则冲突、最大化合并支持数等新最优标准
- 在真实数据集上验证准确率提升与运行效率改善
本文提出ASPEN+，扩展了基于ASP的实体消歧系统ASPEN，新增两大功能：支持局部合并与新的最优解标准。传统ASPEN仅支持全局合并（如作者ID），即所有匹配项统一合并，但实际中局部合并更合理——例如'J. Lee'可能对应'Joy Lee'或'Jake Lee'。ASPEN+允许这种按上下文的局部合并，并引入新优化准则，如最小化规则违反数或最大化支持合并的规则数量。主要贡献包括：(1) 形式化并分析多种最优解概念；(2) 在真实数据集上进行广泛实验，验证局部合并与新准则对准确率和运行时间的影响。
原文摘要 · Abstract (English)
In this paper, we present ASPEN+, which extends an existing ASP-based system, ASPEN,for collective entity resolution with two important functionalities: support for local merges and new optimality criteria for preferred solutions. Indeed, ASPEN only supports so-called global merges of entity-referring constants (e.g. author ids), in which all occurrences of matched constants are treated as equivalent and merged accordingly. However, it has been argued that when resolving data values, local merges are often more appropriate, as e.g. some instances of 'J. Lee' may refer to 'Joy Lee', while others should be matched with 'Jake Lee'. In addition to allowing such local merges, ASPEN+ offers new optimality criteria for selecting solutions, such as minimizing rule violations or maximising the number of rules supporting a merge. Our main contributions are thus (1) the formalisation and computational analysis of various notions of optimal solution, and (2) an extensive experimental evaluation on real-world datasets, demonstrating the effect of local merges and the new optimality criteria on both accuracy and runtime.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。