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基于专利共被引矩阵的物联网技术分析.doc

1、1基于专利共被引矩阵的物联网技术分析摘要:物联网产业被称为继计算机和互联网之后,世界信息产业的第三次浪潮,代表着当前和今后相当一段时间内信息网络的发展方向。然而,我们也必须看到,物联网产业在蓬勃发展的同时也逐渐暴露出了一些问题,如社会各方更多地将注意力集中于物联网概念而轻视其实际应用。基于此,本文借助统计分析方法,对部分企业物联网专利申请情况进行统计,通过专利共被引矩阵、系统聚类分析,进一步明显物联网技术发展现状。 关键词:物联网技术 专利共被引 聚类分析 为了更好地反映物联网产业发展的趋势以及确定物联网关键技术,本课题借助专利数据挖掘方法,对全球物联网产业相关专利技术进行统计分析。 1 专利

2、检索 目前,世界主要发达国家和地区都建立了比较完善的专利数据库,比如德温特(Derwent,全球最权威专利文献出版机构) 、德国专利和商标局专利数据库、美国专利局(USPTO) 、欧洲专利局专利数据库(ESP) 、世界知识产权组织专利数据库(WIPO) 、日本 PAJ 数据库以及中国 CNIPR数据库等。为了便于统计分析,本文选取较为权威的 Derwent 专利数据库作为专利采集来源。 物联网技术主要有感知、传输和处理三个环节构成,其中感知是数2据感知与采集、传输是数据传输,处理则是无线组网与信息处理反馈。本文在阅读核心期刊文献的基础上,确定物联网专利检索关键词:传感(sensor,trans

3、ducer,detector) ,射频技术(RFID) ,微机电系统(mems) ,标签(label,tag,tab) ,读写器(reader) ,二维码(2d barcode) ,定位技术(GPS,location,global positioning system) ,分布式自组网(ad-hoc,mesh) ,超宽带(ultrawideband,uwb) ,无线 usb(wusb) ,蓝牙(bluetooth) ,无线局域网(wireless man,wman) ,近距离无线通信(near field communication,nfc) ,物联网(internet of things,

4、iot, ubiquitous) ,传感网(sensor network)无线传感器网络(wsn) ,拓扑组网(topology+,cluster+) 。 同时,由于物联网技术的集成性,使得相关专利权人非常多,这就给专利共被引矩阵造成很大困难。为此,本课题选取 1976 年以来物联网专利技术影响力较高、且比较典型的 8 家公司作为研究对象,这 8 家企业专利被引证率高,实际上也能够在一定程度反映物联网技术的发展趋势。专利数据检索结果如表 1 所示。 2 专利共被引矩阵分析 专利共被引是指两项专利技术同时被后来的其他专利引用的情况。例如,A、B 两项专利都被专利 C 引用,则可认为专利 A 和

5、B 之间存在共被引关系,这种关系通常被认为是两项技术在理论或方法的表现。通常而言,专利共被引次数多,意味着此项技术较为关键。 本课题以上述 8 位专利权人(8 家企业)作为共被引分析的主体,对其专利被引证信息进行统计并相互对比找出共被引信息,建立共被引矩3阵。 但是,共被引矩阵对角线上的数值代表企业自引的频次,其他数值代表 8 家企业专利共同被引证的频次。同时,共被引频次仅能代表两家企业之间专利被共同引用的绝对值,并不能反映相关联情况,因此,需将共被引矩阵数值转化为无量纲相关系。本文采用国内外学者们惯用的方法,将共被引矩阵转化为 Pearson 相关矩阵。首先,应用 SPSS-Statisti

6、cs 统计分析软件中的 Pearson 相关系数进行双变量相关性分析,最终得到表 2。 3 聚类分析 为了更好地对物联网发展趋势进行分析,本课题借助 SPSS-Statistics 统计分析软件,用系统聚类方法对专利共被引矩阵进行聚类分析。将数据输入软件,得到聚类结果。从聚类分析结果可以看出,8 家企业被分为两个类别:一类是施乐、西门子、柯达公司,以图像采集、定位和处理专利技术为主;二类是镁光科技、IBM、松下电工、摩托罗拉、惠普、东芝,主要专利技术是中间件、通信网络和物联网系统集成。 参考文献: 1杨璧嘉,lhajnrqHnkIbog73lipvmiJDnhp/luqbmqKHlnovnmo

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30、ZPot6/moaXmooHmlr3lt6XlrZjlnKjnmoTpl67popjlkoznrZbnlaUw6K+V5p6Q6YGT6Lev5qGl5qKB5pa95bel5a2Y5Zyo55qE6Zeu6aKY5ZKM562W55WlZAIGD2QWAmYPFQQADHpxZ2wyMDEzMDk4MBvlu7rnrZHnlLXmsJTnmoTotKjph4/mjqfliLYb5bu6562R55S15rCU55qE6LSo6YeP5o6n5Yi2ZAIHD2QWAmYPFQQADHpxZ2wyMDEzMDk4MTnlpKfkvZPnp6/mt7flh53lnJ/mlr3lt6XmioDmn

31、K/lnKjl9u7rnrZHlt6XnqIvkuK3nmoTlupTnlKg55aSn5L2T56ev5re35Yed5Zyf5pa95bel5oqA5pyv5Zyo5bu6562R5bel56iL5Lit55qE5bqU55SoZAIID2QWAmYPFQQADHpxZ2wyMDEzMDk4MiTmtYXosIjpq5jogJDkuYXmgKfmt7flh53lnJ/nmoTphY3liLYk5rWF6LCI6auY6ICQ5LmF5oCn5re35Yed5Zyf55qE6YWN5Yi2ZAIJD2QWAmYPFQQADHpxZ2wyMDEzMDk4Myflhazot6/moaXmooHm

32、lr3lt6XmioDmnK/otKjph4/nmoTmjqLorqgn5YWs6Lev5qGl5qKB5pa95bel5oqA5pyv6LSo6YeP55qE5o6i6K6oZAIFD2QWBGYPFQEM546v5aKD56eR5a2mZAIBDxYCHwECAhYEZg9kFgJmDxUEAAx6cWdsMjAxMzA5ODQk5Lit5Zu95Yac5p2R5rK85rCU5Yip55So5rWF5p6Q5o6i56m2JOS4reWbveWGnOadkeayvOawlOWIqeeUqOa1heaekOaOoueptmQCAQ9kFgJmDxUEAAx6cWdsMjAxMzA5ODUk

33、5rWF6LCI5a+557u/6Imy5bu6562R55qE5Yeg54K55oCd6ICDJOa1heiwiOWvuee7v+iJsuW7uuetkeeahOWHoOeCueaAneiAg2QCBg9kFgRmDxUBDOekvuenkeiuuuWdm2QCAQ8WAh8BAh4WPGYPZBYCZg8VBAAMenFnbDIwMTMwOTg2J+iAgeW5tOaVmeiCsuaEj+S5ieWPiuWFtueJueauiuaAp+iuuueVpSfogIHlubTmlZnogrLmhI/kuYnlj4rlhbbnibnmrormgKforrrnlaVkAgEPZBYCZg8VBAAM

34、enFnbDIwMTMwOTg3M+WGnOadkemlruawtOWuieWFqOW3peeoi+W7uuiuvuS4jueuoeeQhuaooeW8j+eglOeptjPlhpzmnZHppa7msLTlronlhajlt6XnqIvlu7rorr7kuI7nrqHnkIbmqKHlvI/noJTnqbZkAgIPZBYCZg8VBAAMenFnbDIwMTMwOTg4KuWfuuS6juWNmuW8iOinhuinkuiQpemUgOa4oOmBk+ayu+eQhueglOeptirln7rkuo7ljZrlvIjop4bop5LokKXplIDmuKDpgZPmsrvnkIbnoJTn

35、qbZkAgMPZBYCZg8VBAAMenFnbDIwMTMwOTg5OeWFs+S6juW8gOWxleWFmueahOe+pOS8l+i3r+e6v+aVmeiCsuWunui3tea0u+WKqOeahOaAneiAgznlhbPkuo7lvIDlsZXlhZrnmoTnvqTkvJfot6/nur/mlZnogrLlrp7ot7XmtLvliqjnmoTmgJ3ogINkAg10QPZBYCZg8VBAAMenFnbDIwMTMwOTkwPOenkeaKgOWIm+aWsOWKoOW/q+e7j+a1juWPkeWxleaWueW8j+S4reeahOmHkeiejeaUr+aMge

36、aOoueptjznp5HmioDliJvmlrDliqDlv6vnu4/mtY7lj5HlsZXmlrnlvI/kuK3nmoTph5Hono3mlK/mjIHmjqLnqbZkAgUPZBYCZg8VBAAMenFnbDIwMTMwOTkxOeWPjeiFkOWAoeW7ieaVmeiCsuWItuW6puacieaViOaAp+WPkeaMpeeahOe6puadn+S4juWvueetljnlj43ohZDlgKHlu4nmlZnogrLliLbluqbmnInmlYjmgKflj5HmjKXnmoTnuqbmnZ/kuI7lr7nnrZZkAgYPZBYCZg8VBAAMenFnbD

37、IwMTMwOTkyHua1juWNl+S8muWxleS4muernuS6ieWKm+eglOepth7mtY7ljZfkvJrlsZXkuJrnq57kuonlipvnoJTnqbZkAgcPZBYCZg8VBAAMenFnbDIwMTMwOTkzP+WfuuS6juWIqeebiuebuOWFs+iAheWPguS4juS4i+eahOWFrOWPuOayu+eQhumjjumZqeW9seWTjeeglOeptj/ln7rkuo7liKnnm4rnm7jlhbPogIXlj4LkuI7kuIvnmoTlhazlj7jmsrvnkIbpo47pmanlvbHlk43noJTnqbZkAg

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39、YCZg8VBAAMenFnbDIwMTMwOTk2P+WFs+S6juays+WMl+ecgeWQhOWfjuW4guWxheawkeaCo+mrmOihgOWOi+WPiuWFtuWOn+WboOeahOiwg+afpT/lhbPkuo7msrPljJfnnIHlkITln47luILlsYXmsJHmgqPpq5jooYDljovlj4rlhbbljp/lm6DnmoTosIPmn6VkAgsPZBYCZg8VBAAMenFnbDIwMTMwOTk3NuS7juezu+e7n+eQhuiuuuWvueS9k+iCsuW+ruWNmui/m+ihjOekvuS8muWFs+ezu+eglOeptjbku47ns7vnu5/nkIborrrlr7nkvZPogrLlvq7ljZrov5vooYznpL7kvJrlhbPns7vnoJTnqbZkAgwP

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