Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, useruser and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.

No abstract

Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, useruser and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.

The rapid growth of the non-English-speaking Internet population has created a need for better searching and browsing capabilities in languages other than English. However, existing search engines may not serve the needs of many non-English-speaking Internet users. In this paper, we propose a generic and integrated approach to searching and browsing the Internet in a multilingual world. Based on this approach, we have developed the Chinese Business Intelligence Portal (CBizPort), a meta-search engine that searches for business information of mainland China, Taiwan, and Hong Kong. Additional functions provided by CBizPort include encoding conversion (between Simplified Chinese and Traditional Chinese), summarization, and categorization. Experimental results of our user evaluation study show that the searching and browsing performance of CBizPort was comparable to that of regional Chinese search engines, and CBizPort could significantly augment these search engines. Subjects' verbal comments indicate that CBizPort performed best in terms of analysis functions, cross-regional searching, and user-friendliness, whereas regional search engines were more efficient and more popular. Subjects especially liked CBizPort's summarizer and categorizer, which helped in understanding search results. These encouraging results suggest a promising future of our approach to Internet searching and browsing in a multilingual world. IntroductionAs the Internet grows in popularity worldwide, more users want to access Web content in their native languages. A report published in September 2002 shows that the majority of the total global online population (63.5%) lives in non-English-speaking areas (Global-Reach, 2002). Moreover, that population was estimated to grow from 403.5 million in 2002 to 657 million in 2004 (a growth rate of 62.8%), while the population of English-speaking users only will grow from 230.6 million to 280 million during the same period (a growth rate of 21.4%). The lower growth rate of English-speaking online population suggests that the importance of English on the Internet will decline in the future.Instead of relying on English, more non-English-speaking users are expected to use their native languages when searching and browsing the Web. However, existing search engines may not serve their needs, because most technologies have been developed for English-speaking users. To facilitate Internet searching and browsing in a multilingual world, an approach that can be generically applied to any language and that integrates existing search-engine technologies should benefit both business and general users.The Chinese language provides a good example. Chinese is the primary language for people in mainland China, Hong Kong, and Taiwan, where emerging economies are bringing tremendous growth to the Internet population. In mainland China, the number of Internet users has been growing at 65% every 6 months since 1997 (CNNIC, 2002). Taiwan and Hong Kong lead the regions by having the highest Internet penetration rates in the ...

We describe an attempt to overcome information overload through information visualization -in a particular domain, group memory. A brief review of information visualization is followed by a brief description of our methodology. We Ž . discuss our system, which uses multidimensional scaling MDS to visualize relationships between documents, and which Ž . we tested on 60 subjects, mostly students. We found three important and statistically significant differences between task performance on an MDS-generated display and on a randomly generated display. With some qualifications, we conclude that MDS speeds up and improves the quality of manual classification of documents and that the MDS display agrees with subject perceptions of which documents are similar and should be displayed together. q