信息检索报告

2023-01-14 19:44:13   文档大全网     [ 字体: ] [ 阅读: ]

#文档大全网# 导语】以下是®文档大全网的小编为您整理的《信息检索报告》,欢迎阅读!
检索,报告,信息
实习 英文数据库和专利标准检索



实习目的:

1.熟悉部分英文数据库的概况和检索。 2.熟悉专利、标准相关知识及检索。 实习题目:

(一)英文数据库检索

1. ISI Web of Science 数据库,为以下主题(选择一个)查找英文学资料 例:①国内外云计算的研究现状分析; 计算机人脸识别算法研究

③两足机器人的研究

④基于Matlab***模拟(仿真); ⑤家用清扫机器人的设计

⑥基于PLC控制的物料分拣装置设计 按以下步骤完成答题:

1 课题名称:

机器学习应用

2 中英文关键词:、

中文关键词 英文关键词

3 检索式:

主题: (Machine Learning) AND 主题: (application)

4 检索结果(数量、1篇文摘):

检索结果数量 一篇文摘

机器学习 应用

Machine Learning application

6715

: Traditional geostatistical estimation techniques have been used predominantly by the mining industry for ore reserve estimation. Determination of mineral reserve has posed considerable challenge to mining engineers due to the geological complexities of ore body formation. Extensive research over the years has resulted in the development of several state-of-the-art methods for predictive spatial mapping, which could be used for ore reserve estimation; and recent advances in the use of machine learning algorithms (MLA) have provided a new approach for solving the prob-lem of ore reserve estimation. The focus of the present study was on the use of two MLA for estimating ore reserve: namely, neural networks (NN) and support vector


machines (SVM). Application of MLA and the various issues involved with using them for reserve estimation have been elaborated with the help of a complex drill-hole dataset that exhibits the typical properties of sparseness and impreciseness that might be associated with a mining dataset. To investigate the accuracy and applicability of MLA for ore reserve estimation, the generalization ability of NN and SVM was compared with the geostatistical ordinary kriging (OK) method.



5 WOS具有强大的结果分析功能,可用于快速掌握课题研究历史、进展、动

态、前沿、领先者等多种信息,便于科研信息分析。练习:了解对所选课题的研究处于世界领先地位的国家、机构、学者,例举前2 记录数前三名的国家 记录数前三名的机构

25.881 %24.397 %6.772 %

CHINESE ACAD SCI3.154 %CARNEGIE MELLON UNIV1.484 %SHANGHAI JIAO TONG UNIV1.299 %



6)查找机电学院高健教授发表的文章被WOS收录的情况,记录检索式、结果数。 说明:推荐使用CNKI助手(http://dict.cnki.net)帮助确定英文关键词; 检索式:作者: (gao jian)

精炼依据: 作者: ( GAO J ) AND 国家/地区: ( PEOPLES R CHINA OR CHINA )

AND 研究领域: ( SCIENCE TECHNOLOGY ) AND 研究机构:(Guangdong university of technology OR university of Nottingham

时间跨度: 所有年份。 检索语言=自动

结果数:33

(二)专利、标准的基础知识与检索

1.我国专利分三种类型,分别是 发明专利 实用新型专利 外观设计专利

2.查找有关青蒿素专利权归属问题的新闻报道,回答哪国的哪个机构拥有该项专利权?

瑞士诺华公司

3. 查找青岛海尔集团在美国申请的专利数,写出策略和结果数。 198 翻译该公司英文。申请(专利权)人=(Haier) AND 公开国=(US)

4.利用IPC分类检索查找核桃去核取仁机方面的专利,记录检索策略和结果数。 检索式:IPC分类号=(A23N5/00) 结果数:6567

5.通过万方检索出标准GB/T 7714-2005,记录检索策略、该项标准的名称。 检索式:标准:(GB/T 7714-2005


本文来源:https://www.wddqxz.cn/8626079f03d276a20029bd64783e0912a2167c62.html

相关推荐