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Research on Recommendation Method over Always-on Connected broadband Networks.

永远在线连接宽带网络的推荐方法研究。

基本信息

批准号：
16500075
负责人：
TSUDA Kazuhiko
金额：
$ 2.37万
依托单位：
University of TSUKUBA
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2005
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-16500075/
关键词：
broadband Marketing Recommendation Contents P2P

项目摘要

This research will focus on establishing the new recommending methods on the site. Our method is to analyze some information on the web contents. This technology enables us to understand the latest information of each user for the time-series activities. (i.e.the status for transmitting the web contents)The objectives for this research will be defined as follows ;For Contents Holder or Contents AdministatorProvide the correct information for the user preference promptly from the site traces.For login user, Provide the correct information for the user intention. Today, The Contents from the web site system are one of the main purposes to obtain any kind of the information. Therefore, we made some research based on the Natural Language Processing techniques as following issues ;1)The sites access histories for the internet service providers2)The analysts' reports for the stock investment3)The site information for the local governmentsThe results for the above research have reported and made a presentation at the international conference of "KES 2005" and International academic journal of "IJCSNS" It is one of the key technologies for the recommending system to gather any kind of information on the site promptly ; therefore, we made some research for the prompt digital document file share technologies and reported at FIT 2005. Moreover, we have to process the huge size of data immediately to estabilish the above technology, which made us to obtain some technologies for the computer algorithm.As the result, we published out a book concerned with computer algorithm titled "Computer Algorithm" from the Kyoritsu Shuppan publishing company in Tokyo. From the above research activities, we have reached diverse (or wide range of) results not only key technologies but the applied ones. We conclude with our vision for preceding the advanced research based on the above research activities for the future research activities.

本研究将致力于建立新的网站推荐方法。我们的方法是分析网页内容上的一些信息。这项技术使我们能够了解每个用户的最新信息的时间序列的活动。（即传输网页内容的状态）本研究的目标将被定义如下：对于内容保持器或内容管理员提供正确的信息为用户的喜好，及时从网站的痕迹。对于登录用户，提供正确的信息为用户的意图。今天，从网站系统中获取内容是获取任何类型信息的主要目的之一。因此，本文在自然语言处理技术的基础上，对以下几个问题进行了研究：1）互联网服务提供商的网站访问历史2）股票投资分析报告3）地方政府的网站信息上述研究结果已在“KES 2005”国际会议和“IJCSNS”国际学术期刊上报告和发表。快速收集网站上的各种信息是推荐系统的关键技术之一，因此，我们对快速数字文档文件共享技术进行了研究，并在FIT 2005上进行了报告。而且，我们必须立即处理大量的数据来建立上述技术，这使得我们获得了计算机算法的一些技术，因此，我们在东京的Kyoritsu Shuppan出版公司出版了一本关于计算机算法的书，名为“Computer Algorithm”。通过上述研究活动，我们不仅获得了关键技术，而且还获得了应用技术。最后，我们展望了未来的研究活动的基础上，上述研究活动的先进研究。