Exploring Social Annotations with the Application to Web Page Recommendation

Collaborative social annotation systems allow users to record and share their original keywords or tag attachments to Web resources such as Web pages, photos, or videos. These annotations are a method for organizing and labeling information. They have the potential to help users navigate the Web and locate the needed resources. However, since annotations axe posted by users under no central control, there exist problems such as spare and synonymous annotations. To efficiently use annotation information to facilitate knowledge discovery from the Web, it is advantageous if we organize social annotations from semantic perspective and embed them into algorithms for knowledge discovery. This inspires the Web page recommendation with annotations, in which users and Web pages are clustered so that semantically similar items can be related. In this paper we propose four graphic models which cluster users, Web pages and annotations and recommend Web pages for given users by assigning items to the right cluster first. The algorithms are then compared to the classical collaborative filtering recommendation method on a real-world data set. Our result indicates that the graphic models provide better recommendation performance and are robust to fit for the real applications.

Collective Intelligence and Uncertain Knowledge Representation in Cloud Computing

The lasting evolution of computing environment, software engineering and interaction methods leads to cloud computing. Cloud computing changes the configuration mode of resources on the Internet and all kinds of resources are virtualized and provided as services. Mass participation and online interaction with social annotations become usual in human daily life. People who own similar interests on the Internet may cluster naturally into scalable and boundless communities and collective intelligence will emerge. Human is taken as an intelligent computing factor, and uncertainty becomes a basic property in cloud computing. Virtualization, soft computing and granular computing will become essential features of cloud computing. Compared with the engineering technological problems of IaaS (Infrastructure as a service), PaaS (Platform as a Service) and SaaS (Software as a Service), collective intelligence and uncertain knowledge representation will be more important frontiers in cloud computing for researchers within the community of intelligence science.

A Tag-based way of organizing and exploring literature resources in Web 2.0 environment

With the rapid development of Web2.0 technology, more and more social annotation systems are emerging, such as Del.icio.us, Flickr, YouTube, and CiteULike. These systems help users to manage and share their digital resources, and have attracted a lot of users to annotate the resources with tags and bookmarks, which result in a large scale of tag data. Due to the exponential increase of social annotations, all the users are facing the same problem: How can we explore the desired resources efficiently in such a large tag dataset? Since the traditional methods such as tag cloud view and annotation match work well only in small annotation dataset, this paper studies the relationships of tag-tag, tag-resource and resource-resource through the co-occurrences and proposes a new efficient way for users to organize and explore the literature resources. Our research mainly focuses on two aspects:1) The hidden semantic relationships of popular tags and their relevant literature resources;2) the computing of literature resources similarity given a specific literature. A prototype system named PKUSpace is implemented and shows promising results.