摘要翻译：
PDM系统包含和管理着大量的数据，但大多数系统的搜索机制并不智能化，无法处理用户基于自然语言的查询，从而提取出所需的信息。目前，几乎所有PDM系统中的搜索机制都不是很有效，而是基于旧的搜索方式，通过将相关信息输入到搜索表单的各个字段中，从附加的存储库中找出一些特定的信息。针对这一问题，本文从PDM系统和语言技术两个方面进行了深入的研究。在PDM系统方面，进行了详细的研究，提供了关于PDM和PDM系统的信息。在语言技术领域，通过分析用户基于自然语言的请求，帮助实现PDM系统的搜索机制，以搜索用户需要的信息。本研究的目标是为PDM领域提供一个新的概念模型，以实现基于自然语言的搜索。所提出的概念模型被成功地设计并以原型的形式部分实现。本文详细描述了该方法的主要概念、实现设计和开发原型。将实现的原型与现有PDM系统Windchill和CIM的各自功能进行比较，以评估其针对目标挑战的有效性。
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英文标题：
《Proposing LT based Search in PDM Systems for Better Information
  Retrieval》
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作者：
Zeeshan Ahmed
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Information Retrieval        信息检索
分类描述：Covers indexing, dictionaries, retrieval, content and analysis. Roughly includes material in ACM Subject Classes H.3.0, H.3.1, H.3.2, H.3.3, and H.3.4.
涵盖索引，字典，检索，内容和分析。大致包括ACM主题课程H.3.0、H.3.1、H.3.2、H.3.3和H.3.4中的材料。
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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。
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英文摘要：
  PDM Systems contain and manage heavy amount of data but the search mechanism of most of the systems is not intelligent which can process user"s natural language based queries to extract desired information. Currently available search mechanisms in almost all of the PDM systems are not very efficient and based on old ways of searching information by entering the relevant information to the respective fields of search forms to find out some specific information from attached repositories. Targeting this issue, a thorough research was conducted in fields of PDM Systems and Language Technology. Concerning the PDM System, conducted research provides the information about PDM and PDM Systems in detail. Concerning the field of Language Technology, helps in implementing a search mechanism for PDM Systems to search user"s needed information by analyzing user"s natural language based requests. The accomplished goal of this research was to support the field of PDM with a new proposition of a conceptual model for the implementation of natural language based search. The proposed conceptual model is successfully designed and partially implementation in the form of a prototype. Describing the proposition in detail the main concept, implementation designs and developed prototype of proposed approach is discussed in this paper. Implemented prototype is compared with respective functions of existing PDM systems .i.e., Windchill and CIM to evaluate its effectiveness against targeted challenges.
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PDF链接：
https://arxiv.org/pdf/1102.1803