Content and expression-based copy recognition for intellectual property protection

Özlem Uzuner, Randall Davis
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引用次数: 11

Abstract

Protection of copyrights and revenues of content owners in the digital world has been gaining importance in the recent years. This paper presents a way of fingerprinting text documents that can be used to identify content and expression similarities in documents, as a way of facilitating tracking of digital copies of works, to ensure proper compensation to content owners.The fingerprints we collected consist of surface, syntactic, and semantic features of documents. Because they reflect mostly how things are said, we call these features stylistic fingerprints. However, how things are said are not independent of what is said, therefore these features have predictive power with respect to both content and expression.We tested the ability of these stylistic fingerprints to identify content and expression similarities between documents using a corpus of translated novels. On this corpus, these fingerprints identified the source of a given book chapter (content) successfully 90% of the time and the translator of the chapter (expression) 67% of the time using ten-fold cross validation and decision trees.In comparison, fingerprints based on the vocabularies of documents recognized the source of a given book chapter accurately 93% of the time and the expression of a particular translator 61% of the time.We believe that the right fingerprints can identify modified and literal copies of works, securing revenues for content owners. Enabling the content owners to secure revenues from distribution of their works can alleviate the digital copyright problem and reduce the need to prevent distribution, giving a chance to solutions that promote uninhibited distribution and use of works by the public.
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基于内容和表达的知识产权保护复制识别
近年来,保护数字世界的版权和内容所有者的收入变得越来越重要。本文提出了一种文本文档指纹识别方法,可用于识别文档中的内容和表达相似性,以方便对作品的数字副本进行跟踪,以确保对内容所有者进行适当的补偿。我们收集的指纹包括文档的表面、语法和语义特征。因为它们主要反映了说话的方式,我们把这些特征称为风格指纹。然而,说话的方式并不独立于所说的内容,因此这些特征在内容和表达方面都具有预测能力。我们使用翻译的小说语料库测试了这些风格指纹识别文档之间内容和表达相似性的能力。在这个语料库上,使用十倍交叉验证和决策树,这些指纹识别出给定书籍章节(内容)的来源的成功率为90%,章节(表达)的译者的成功率为67%。相比之下,基于文件词汇表的指纹识别给定书籍章节来源的准确率为93%,特定译者的表达准确率为61%。我们相信,正确的指纹可以识别作品的修改和文字副本,为内容所有者确保收入。使内容所有者能够从其作品的发行中获得收入,可以缓解数字版权问题,减少防止发行的需要,从而为促进公众不受限制地分发和使用作品的解决方案提供机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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