基于互联网的研究者兴趣挖掘

Song Kang, Nanchang Cheng
{"title":"基于互联网的研究者兴趣挖掘","authors":"Song Kang, Nanchang Cheng","doi":"10.1109/DSA.2019.00011","DOIUrl":null,"url":null,"abstract":"In today's knowledge-based economy society, the rapid spread of a trend, personalized knowledge service has become the mainstream of development, so that the Web information users can meet the variety, high level of precision and content requirements of the high-level service form. Through analysis, we can find that the mining of researchers' interest can serve as the main learning content of personalized knowledge services. So the realization of research interest mining based on Internet is to meet the special information needs of the users, which can be called an effective method to optimize the content of personalized business. Therefore, a more effident algorithm is used to optimize the search search program for Internet information and improve the search efficiency. This optimization can become the research direction of the present age of all things in the world. The information data mining strategy to the simple to can improve the information retrieval efficiency of the network resources, and can provide the accurate, reliable summary of the Internet information resources, meet the convenience and precision of the researchers to retrieve the Internet information resources, thus can be accurate and high. The research interest mining based on the Internet includes the use of search engines to obtain the relevant information of the researchers. Through data mining and machine learning algorithms, the results information returned by the search engine are analyzed, and the research interests of the researchers are obtained from the contents of these results.","PeriodicalId":342719,"journal":{"name":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Internet-Based Researcher Interest Mining\",\"authors\":\"Song Kang, Nanchang Cheng\",\"doi\":\"10.1109/DSA.2019.00011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In today's knowledge-based economy society, the rapid spread of a trend, personalized knowledge service has become the mainstream of development, so that the Web information users can meet the variety, high level of precision and content requirements of the high-level service form. Through analysis, we can find that the mining of researchers' interest can serve as the main learning content of personalized knowledge services. So the realization of research interest mining based on Internet is to meet the special information needs of the users, which can be called an effective method to optimize the content of personalized business. Therefore, a more effident algorithm is used to optimize the search search program for Internet information and improve the search efficiency. This optimization can become the research direction of the present age of all things in the world. The information data mining strategy to the simple to can improve the information retrieval efficiency of the network resources, and can provide the accurate, reliable summary of the Internet information resources, meet the convenience and precision of the researchers to retrieve the Internet information resources, thus can be accurate and high. The research interest mining based on the Internet includes the use of search engines to obtain the relevant information of the researchers. Through data mining and machine learning algorithms, the results information returned by the search engine are analyzed, and the research interests of the researchers are obtained from the contents of these results.\",\"PeriodicalId\":342719,\"journal\":{\"name\":\"2019 6th International Conference on Dependable Systems and Their Applications (DSA)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 6th International Conference on Dependable Systems and Their Applications (DSA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DSA.2019.00011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 6th International Conference on Dependable Systems and Their Applications (DSA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DSA.2019.00011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在当今知识经济社会迅速蔓延的一种趋势中,个性化的知识服务已成为发展的主流,使Web信息能够满足用户对服务形式的多样化、高精度和内容高水平的要求。通过分析可以发现,研究者兴趣的挖掘可以作为个性化知识服务的主要学习内容。因此,基于Internet的研究兴趣挖掘的实现是为了满足用户的特殊信息需求,是一种优化个性化业务内容的有效方法。因此,采用一种更有效的算法来优化网络信息搜索程序,提高搜索效率。这种优化可以成为当今世界万物时代的研究方向。该信息数据挖掘策略力求简单,能够提高网络资源的信息检索效率,并能提供准确、可靠的互联网信息资源汇总,满足研究人员检索互联网信息资源的便利性和精确性,从而能够准确、高。基于Internet的研究兴趣挖掘包括利用搜索引擎获取研究人员的相关信息。通过数据挖掘和机器学习算法,对搜索引擎返回的结果信息进行分析,并从这些结果的内容中获得研究人员的研究兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Internet-Based Researcher Interest Mining
In today's knowledge-based economy society, the rapid spread of a trend, personalized knowledge service has become the mainstream of development, so that the Web information users can meet the variety, high level of precision and content requirements of the high-level service form. Through analysis, we can find that the mining of researchers' interest can serve as the main learning content of personalized knowledge services. So the realization of research interest mining based on Internet is to meet the special information needs of the users, which can be called an effective method to optimize the content of personalized business. Therefore, a more effident algorithm is used to optimize the search search program for Internet information and improve the search efficiency. This optimization can become the research direction of the present age of all things in the world. The information data mining strategy to the simple to can improve the information retrieval efficiency of the network resources, and can provide the accurate, reliable summary of the Internet information resources, meet the convenience and precision of the researchers to retrieve the Internet information resources, thus can be accurate and high. The research interest mining based on the Internet includes the use of search engines to obtain the relevant information of the researchers. Through data mining and machine learning algorithms, the results information returned by the search engine are analyzed, and the research interests of the researchers are obtained from the contents of these results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信