Multiresolution spatial databases: Making web-based spatial advances faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

The next generation messaging technology: Makes web services effective

The vision presented in this paper and its technical content are a result of close collaboration between several researchers from the University of Queensland, Australia and the SAP Corporate Research Center, Brisbane, Australia. In particular; Dr Wasim Sadiq (SAP), Dr Shazia Sadiq (UQ), and Dr Karsten Schultz (SAP) are the prime contributors to the ideas presented. Also, PhD students Mr Dat Ma Cao and Ms Belinda Carter are involved in the research program. Additionally, the Australian Research Council Discovery Project Scheme and Australian Research Council Linkage Project Scheme support some aspects of research work towards the HMT solution.

Reflective web interface agent

Web interface agent is used with web browsers to assist users in searching and interactions with the WWW. It is used for a variety of purposes, such as web-enabled remote control, web interactive visualization, and e-commerce activities. User may be aware or unaware of its existence. The intelligence of interface agent consists in its capability of learning and decision-making in performing interactive functions on behalf of a user. However, since web is an open system environment, the reasoning mechanism in an agent should be able to adapt changes and make decisions on exceptional situations, and therefore use meta knowledge. This paper proposes a framework of Reflective Web Interface Agent (RWIA) that is to provide causal connections between the application interfaces and the knowledge model of the interface agent. A prototype is also implemented for the purpose of demonstration.

Searching the world wide web for local services and facilities: A review on the patterns of location-based queries

Many queries sent to search engines refer to specific locations in the world. Location-based queries try to find local services and facilities around the user’s environment or in a particular area. This paper reviews the specifications of geospatial queries and discusses the similarities and differences between location-based queries and other queries. We introduce nine patterns for location-based queries containing either a service name alone or a service name accompanied by a location name. Our survey indicates that at least 22% of the Web queries have a geospatial dimension and most of these can be considered as location-based queries. We propose that location-based queries should be treated different from general queries to produce more relevant results.

A web recommendation technique based on probabilistic latent semantic analysis

Web transaction data between Web visitors and Web functionalities usually convey user task-oriented behavior pattern. Mining such type of click-stream data will lead to capture usage pattern information. Nowadays Web usage mining technique has become one of most widely used methods for Web recommendation, which customizes Web content to user-preferred style. Traditional techniques of Web usage mining, such as Web user session or Web page clustering, association rule and frequent navigational path mining can only discover usage pattern explicitly. They, however, cannot reveal the underlying navigational activities and identify the latent relationships that are associated with the patterns among Web users as well as Web pages. In this work, we propose a Web recommendation framework incorporating Web usage mining technique based on Probabilistic Latent Semantic Analysis (PLSA) model. The main advantages of this method are, not only to discover usage-based access pattern, but also to reveal the underlying latent factor as well. With the discovered user access pattern, we then present user more interested content via collaborative recommendation. To validate the effectiveness of proposed approach, we conduct experiments on real world datasets and make comparisons with some existing traditional techniques. The preliminary experimental results demonstrate the usability of the proposed approach.

Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.

Towards more personalized web: Extraction and integration of dynamic content from the Web

Information and content integration are believed to be a possible solution to the problem of information overload in the Internet. The article is an overview of a simple solution for integration of information and content on the Web. Previous approaches to content extraction and integration are discussed, followed by introduction of a novel technology to deal with the problems, based on XML processing. The article includes lessons learned from solving issues of changing webpage layout, incompatibility with HTML standards and multiplicity of the results returned. The method adopting relative XPath queries over DOM tree proves to be more robust than previous approaches to Web information integration. Furthermore, the prototype implementation demonstrates the simplicity that enables non-professional users to easily adopt this approach in their day-to-day information management routines.

Calculation of target locations for web resources

A location-based search engine must be able to find and assign proper locations to Web resources. Host, content and metadata location information are not sufficient to describe the location of resources as they are ambiguous or unavailable for many documents. We introduce target location as the location of users of Web resources. Target location is content-independent and can be applied to all types of Web resources. A novel method is introduced which uses log files and IN to track the visitors of websites. The experiments show that target location can be calculated for almost all documents on the Web at country level and to the majority of them in state and city levels. It can be assigned to Web resources as a new definition and dimension of location. It can be used separately or with other relevant locations to define the geography of Web resources. This compensates insufficient geographical information on Web resources and would facilitate the design and development of location-based search engines.