摘要翻译：
在许多场景中，如紧急响应或ad hoc协作，降低集成数据的开销是至关重要的。理想情况下，可以在一个统一的接口下交互地执行整个过程：为源定义提取器和包装器，创建中介模式，并添加模式映射？同时了解这些如何影响数据的集成视图，并相应地改进设计。我们提出了一种新的智能复制和粘贴(SCP)模型和体系结构，用于无缝地结合数据集成的设计时和运行时两个方面，并描述了一个初始原型CopyCat系统。在CopyCat中，用户不需要用于不同集成阶段的特殊工具：相反，系统监视用户从应用程序（包括Web浏览器）复制数据并将其粘贴到CopyCat的类似电子表格的工作区中。CopyCat概括了这些动作，并提出了建议的自动完成，每个都以出处的形式给出了解释。用户对这些建议提供反馈？通过直接交互或进一步的复制粘贴操作？系统从这个反馈中学习。本文概述了我们的原型系统，并确定了在实现SCP的通用性方面的关键研究挑战。
---
英文标题：
《Interactive Data Integration through Smart Copy & Paste》
---
作者：
Zachary Ives (University Of Pennsylvania), Craig Knoblock (University
  of Southern California - Information Sciences Institute), Steve Minton (Fetch
  Technologies), Marie Jacob (University of Pennsylvania), Partha Talukdar
  (University of Pennsylvania), Rattapoom Tuchinda (University of Southern
  California - Information Sciences Institute), Jose Luis Ambite (University of
  Southern California - Information Sciences Institute), Maria Muslea
  (University of Southern California - Information Sciences Institute), Cenk
  Gazen (Fetch Technologies)
---
最新提交年份：
2009
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Databases        数据库
分类描述：Covers database management, datamining, and data processing. Roughly includes material in ACM Subject Classes E.2, E.5, H.0, H.2, and J.1.
涵盖数据库管理、数据挖掘和数据处理。大致包括ACM学科类E.2、E.5、H.0、H.2和J.1中的材料。
--
一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  In many scenarios, such as emergency response or ad hoc collaboration, it is critical to reduce the overhead in integrating data. Ideally, one could perform the entire process interactively under one unified interface: defining extractors and wrappers for sources, creating a mediated schema, and adding schema mappings ? while seeing how these impact the integrated view of the data, and refining the design accordingly.   We propose a novel smart copy and paste (SCP) model and architecture for seamlessly combining the design-time and run-time aspects of data integration, and we describe an initial prototype, the CopyCat system. In CopyCat, the user does not need special tools for the different stages of integration: instead, the system watches as the user copies data from applications (including the Web browser) and pastes them into CopyCat?s spreadsheet-like workspace. CopyCat generalizes these actions and presents proposed auto-completions, each with an explanation in the form of provenance. The user provides feedback on these suggestions ? through either direct interactions or further copy-and-paste operations ? and the system learns from this feedback. This paper provides an overview of our prototype system, and identifies key research challenges in achieving SCP in its full generality.
---
PDF链接：
https://arxiv.org/pdf/0909.1769