Machine Learning for User Modeling

At first blush, user modeling appears to be a prime candidate for straightforward application of standard machine learning techniques. Observations of the user's behavior can provide training examples that a machine learning system can use to form a model designed to predict future actions. However, user modeling poses a number of challenges for machine learning that have hindered its application in user modeling, including: the need for large data sets; the need for labeled data; concept drift; and computational complexity. This paper examines each of these issues and reviews approaches to resolving them.     

Fuzzy User Modeling for Information Retrieval on the World Wide Web

Information retrieval from the World Wide Web through the use of search engines is known to be unable to capture effectively the information needs of users. The approach taken in this paper is to add intelligence to information retrieval from the World Wide Web, by the modeling of users to improve the interaction between the user and information retrieval systems. In other words, to improve the performance of the user in retrieving information from the information source. To effect such an improvement, it is necessary that any retrieval system should somehow make inferences concerning the information the user might want. The system then can aid the user, for instance by giving suggestions or by adapting any query based on predictions furnished by the model. So, by a combination of user modeling and fuzzy logic a prototype system has been developed (the Fuzzy Modeling Query Assistant (FMQA)) which modifies a user's query based on a fuzzy user model. The FMQA was tested via a user study which clearly indicated that, for the limited domain chosen, the modified queries are better than those that are left unmodified. Received 10 November 1998 / Revised 14 June 2000 / Accepted in revised form 25 September 2000     

Web站点的超链结构挖掘

ＷＷＷ是一个由成千上万个分布在世界各地的Ｗｅｂ站点组成的全球信息系统,每个Ｗｅｂ站点又是一个由许多Ｗｅｂ页构成的信息（子）系统。由于一个文档作者可以通过超链把自己的文档与任意一个已知的Ｗｅｂ页链接起来,而一个 Ｗｅｂ站点上的信息资源又通常是由许多人共同提供的, 因此 Ｗｅｂ站点内的超链链接通常是五花八门、各种各样的,它们可以有各种含义和用途。文章分析了ＷＷＷ系统中超链的使用特征和规律,提出了一个划分超链类型、挖掘站点结构的方法,初步探讨了它在信息收集和查询等方面的应用。     

面向Web的信息收集工具的设计与开发

随着互联网的发展以及网上信息的日益丰富 ,传统的信息处理已经延伸到互联网领域。在对互联网上的信息进行处理时 ,常常要将分布在互联网各处的Web页面下载到本地供进一步处理 ;这便是所讨论的Web页面收集工具的核心功能。该页面收集系统在综合使用Web页面间的链接关系和页面内容的基础上 ,增加了多层次的页面过滤模块 ,可用来收集特定领域内的Web页面 ;同时可采用多机并行收集的方法提高页面收集的效率 ;采用大型数据库存放元收集信息 ,并对收集到的页面进行压缩 ,能够支持海量数据的收集 ;动态更新机制的实施使得下载到本地的页面信息能够得到及时的更新。     

The Best Web Sites in Psychology and Sociology

Abstract

The World Wide Web offers a large and ever-expanding number of resources in the fields of psychology and sociology. Growth of the Web has been so fast that it has been difficult to keep track of all the new resources that are rapidly becoming available. With so many new Web sites cropping up, there is a growing need to sort through these resources and determine which sites are the most valuable for research in these subject areas. This study first discusses some criteria for assessing the quality of Web sites, and then applies these criteria to the Web sites currently available in an effort to determine which sites are the best for these two fields.     

Information gathering and searching approaches on the Web

The information accessible through the Internet is increasing explosively as the Web is getting more and more widespread. In this situation, the Web is indispensable information resource for both of information gathering and information searching. Though traditional information retrieval techniques have been applied to information gathering and searching in the Web, they are insufficient for this new form of information source. Fortunately some Al techniques can be straightforwardly applicable to such tasks in the Web, and many researchers are trying this approach. In this paper, we attempt to describe the current state of information gathering and searching technologies in the Web, and the application of AI techniques in the fields. Then we point out limitations of these traditional and AI approaches and introduce two aapproaches: navigation planning and a Mondou search engine for overcoming them. The navigation planning system tries to collect systematic knowledge, rather than Web pages, which are only pieces of knowledge. The Mondou search engine copes with the problems of the query expansion/modification based on the techniques of text/web mining and information visualization. Seiji Yamada, Dr. Eng.: He received the B.S., M.S. and Ph.S. degrees in control engineering and artificial intelligence from Osaka University, Osaka, Japan, in 1984, 1986 and 1989, respectively. From 1989 to 1991, he served as a Research Associate in the Department of Control Engineering at Osaka University. From 1991 to 1996, he served as a Lecturer in the Institute of Scientific and Industrial Research at Osaka University. In 1996, he joined the Department of Computational Intelligence and Systems Science at Tokyo Institute of Technology, Yokohama, Japan, as an Associate Professor. His research interests include artificial intelligence, planning, machine learning for a robotics, intelligent information retrieval in the WWW, human computer interaction, He is a member of AAAI, IEEE, JSAI, RSJ and IEICE. Hiroyuki Kawano, Dr.Eng.: He is an Associate Professor at the Department of Systems Science, Graduate School of Informatics, Kyoto University, Japan. He obtained his B.Eng. and M.Eng. degrees in Applied Mathematics and Physics, and his Dr.Eng. degree in Applied Systems Science from Kyoto University. His research interests are in advanced database technologies, such as data mining, data warehousing, knowledge discovery and web search engine (Mondou). He has served on the program committees of several conferences in the areas of Data Base Systems, and technical committes of advanced information systems.     

语义网起源与发展研究

在对目前Web存在的主要问题进行了分析的基础上,介绍语义网,并针对语义网优势和特征进行了论述,展望了语义网的发展前景。     

相关主题的最具权威的Web页搜索

为搜索相关主题最具权威的Web信息资源,提出了一种计算Web页权威值的算法。该算法改进了HITS^[1]算法,无须用户提供关键词,采用由Web例子页的连接扩展获得相关主题的例子页集,用一个Web页被超链接引用的次数来度量该页的权威性。     

How students evaluate information and sources when searching the World Wide Web for information

The World Wide Web (WWW) has become the biggest information source for students while solving information problems for school projects. Since anyone can post anything on the WWW, information is often unreliable or incomplete, and it is important to evaluate sources and information before using them. Earlier research has shown that students have difficulties with evaluating sources and information. This study investigates the criteria secondary educational students use while searching the Web for information. 23 students solved two information problems while thinking aloud. After completing the tasks they were interviewed in groups on their use of criteria. Results show that students do not evaluate results, source and information very often. The criteria students mention when asked which criteria are important for evaluating information are not always the same criteria they mention while solving the information problems. They mentioned more criteria but also admitted not always using these criteria while searching the Web.     

An Examination of Library World Wide Web Sites at Medium-Sized Universities

ABSTRACT

This article presents the results of a study of World Wide Web (Web) Sites for 133 academic libraries serving medium-sized universities. Each library Web site was examined, and all of the features were recorded. The study identified 31 core components which were present in over 50 percent of the libraries surveyed. The study indicated that: the navigational and design aspects of library Web sites should be improved; materials should be placed on the sites only if they will be accessed and utilized by the user community; and libraries could profit by making greater use of online tutorials and virtual tours to supplement regular bibliographic instruction.