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Retrieval of Patent Documents from Heterogeneous Sources Using Ontologies and Similarity Analysis

机译:使用本体和相似性分析从异质源检索专利文献

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In the past few years, there has been an explosive growth in scientific and legal information related to the patent system. Patents and related documents are siloed into multiple heterogeneous sources. Retrieving relevant information from diverse sources is a non-trivial task and poses many technical challenges. Among the challenges is the issue of terminological inconsistencies that are used in the documents. We tackle the terminological inconsistency issue by exploring domain knowledge through the use of ontology standards. Furthermore, we take advantage of cross-references and structural dependencies between the information sources to enhance terminological comparison. In this paper, we present a similarity analysis methodology which combines knowledge from two distinct sources -- (1) domain ontologies and (2) ontologies which describe the information sources to assist a user in identifying relevant documents across several information sources simultaneously. Specifically, we explore the use of a rule-based system to infer relationships between documents based on pre-defined heuristics. We present our results through a use case in the bio-patent domain with a collection of 1150 patents and 30 court cases.
机译:在过去几年中,与专利制度相关的科学和法律信息存在爆炸性增长。专利和相关文件静脉化为多种异质源。从各种来源检索相关信息是一个非琐碎的任务,造成许多技术挑战。在挑战之中是文件中使用的术语不一致的问题。我们通过使用本体标准探索域知识来解决术语不一致问题。此外,我们利用信息来源之间的交叉引用和结构依赖性来提高术语比较。在本文中,我们提出了一种相似性分析方法,其将来自两个不同的源源 - (1)域在本体论和(2)的本体中的知识结合了,该本体描述了信息源,以帮助用户同时识别多个信息源的相关文档。具体而言,我们探讨基于规则的系统使用基于预定义启发式的文档之间的关系推断。我们在生物专利领域的用例介绍了我们的结果,其中包括1150项专利和30项法院案件。

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