哪位好心人帮我翻译一下英文谢谢,不要用机器翻译可以吗Finding all patents relevant to a particular invention inthe vast amount of documents available in the many existingpatent databases is a difficult task. Moreover, missing ju

哪位好心人帮我翻译一下英文谢谢,不要用机器翻译可以吗Finding all patents relevant to a particular invention inthe vast amount of documents available in the many existingpatent databases is a difficult task. Moreover, missing ju
哪位好心人帮我翻译一下英文谢谢,不要用机器翻译可以吗
Finding all patents relevant to a particular invention in
the vast amount of documents available in the many existing
patent databases is a difficult task. Moreover, missing just a single relevant patent, and thus violating intellectual
property (IP) rights of others, can be very expensive for
a company when introducing a new product on the market
that uses an already patented technology. Thus, professional
patent searchers are forced to read (or at least skim
through) all retrieved documents, because the relevant one
could be at the bottom of the search result list. This clearly
contrasts Web users posing ad-hoc queries to Web search
engines who hardly ever look further than at the ten topranked
results. Patent classification systems such as the
International Patent Classification (IPC) maintained by the
World Intellectual Property (WIPO) are important structural
instruments for organizing patents into taxonomies of
technology domains. These taxonomies allow searchers to
constrain search queries to particular technological fields in
order to reduce the amount of documents to be read.
However, these classification schemes have been built by
experts for experts. A more general taxonomy would make
it easier for non-expert users of patent information systems
to access and navigate through the information space. Such
non-experts might not be familiar with the definitions of the
section, classes and subclasses, groups and subgroups contained
in the IPC, but usually are familiar with the subject
matter of the invention or an idea itself, i.e. the scientific
background. To this end, we have created such a taxonomy,
the Wikipedia Science Ontology (WikiSCION), based
on the Wikipedia Science Portal, which is a well-maintained
starting point for a top-down discovery of Science as topic of
interest and its many subtopics. The Wikipedia can be seen
as a source of knowledge crafted, shaped and maintained
by a large community agreeing on a language that is supposed
to be easier to comprehend by non-experts. We have
developed a method for automatically assigning patent documents
to the classes of this taxonomy, and thus enriching
the patents with additional meta-information.
长了点,不过对我很重要

哪位好心人帮我翻译一下英文谢谢,不要用机器翻译可以吗Finding all patents relevant to a particular invention inthe vast amount of documents available in the many existingpatent databases is a difficult task. Moreover, missing ju
Finding all patents relevant to a particular invention in
the vast amount of documents available in the many existing
patent databases is a difficult task.Moreover,missing just a single relevant patent,and thus violating intellectual
property (IP) rights of others,can be very expensive for
a company when introducing a new product on the market
that uses an already patented technology.Thus,professional
patent searchers are forced to read (or at least skim
through) all retrieved documents,because the relevant one
could be at the bottom of the search result list.This clearly
contrasts Web users posing ad-hoc queries to Web search
engines who hardly ever look further than at the ten topranked
results.Patent classification systems such as the
International Patent Classification (IPC) maintained by the
World Intellectual Property (WIPO) are important structural
instruments for organizing patents into taxonomies of
technology domains.These taxonomies allow searchers to
constrain search queries to particular technological fields in
order to reduce the amount of documents to be read.
However,these classification schemes have been built by
experts for experts.A more general taxonomy would make
it easier for non-expert users of patent information systems
to access and navigate through the information space.Such
non-experts might not be familiar with the definitions of the
section,classes and subclasses,groups and subgroups contained
in the IPC,but usually are familiar with the subject
matter of the invention or an idea itself,i.e.the scientific
background.To this end,we have created such a taxonomy,
the Wikipedia Science Ontology (WikiSCION),based
on the Wikipedia Science Portal,which is a well-maintained
starting point for a top-down discovery of Science as topic of
interest and its many subtopics.The Wikipedia can be seen
as a source of knowledge crafted,shaped and maintained
by a large community agreeing on a language that is supposed
to be easier to comprehend by non-experts.We have
developed a method for automatically assigning patent documents
to the classes of this taxonomy,and thus enriching
the patents with additional meta-information.

你干什么用？

找到所有相关的专利发明在某一特定
大量的文件可以在许多现有的
专利数据库是一项艰巨的任务。此外，失踪只是一个单一的相关专利，从而侵犯
知识产权（ IP ）他人的权利，可以是非常昂贵的
当一家公司推出一种新产品在市场上
利用已经获得专利的技术。因此，专业
专利搜索被迫阅读（或至少脱脂
通过）全部取自文件，因为相关的一
可...

全部展开

找到所有相关的专利发明在某一特定
大量的文件可以在许多现有的
专利数据库是一项艰巨的任务。此外，失踪只是一个单一的相关专利，从而侵犯
知识产权（ IP ）他人的权利，可以是非常昂贵的
当一家公司推出一种新产品在市场上
利用已经获得专利的技术。因此，专业
专利搜索被迫阅读（或至少脱脂
通过）全部取自文件，因为相关的一
可能是底部的搜索结果清单。这显然
对比网络用户带来了特设查询网络搜索
发动机谁几乎进一步研究比10 topranked
结果。专利分类系统，如
国际专利分类（ IPC ）的保持
世界知识产权组织世界知识产权组织（ WIPO ）的重要结构
文书组织专利纳入分类的
技术领域。这些分类法允许查询
限制搜索查询特定技术领域的
为了减少文件的数量来阅读。
然而，这些分类计划已建成的
专家的专家。一个更普遍的分类将使
方便非专业用户的专利信息系统
访问和浏览信息空间。这种
非专家可能不熟悉的定义
科类和子类，组和分组载
在IPC的，但通常都熟悉的主题
事项的发明或者一个想法本身，即科学
背景。为此，我们建立这样一个分类，
维基百科科学本体论（ WikiSCION ） ，基于
关于维基百科科学门户，这是一个保存完好的
起点自上而下发现的科学话题
利息和许多分主题。维基百科可以看出
作为设计的知识来源，形成和保持
由大型社会商定的语言，理应
要更容易理解的非专家。我们已
开发了一个方法，自动指派专利文件
在这个类别的分类，从而丰富
专利的额外的元信息。

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