An Application of Collaborative Web Browsing Based on Ontology Learning from User Activities on the Web

With explosively increasing amount of information on the Web, users have been getting more bored to seek relevant information. Several studies have introduced adaptive approaches to recognizing personal interests. This paper proposes the collaborative Web browsing system that can support users to share knowledge with other users. Especially, we have focused on user interests extracted from their own activities related to bookmarks. A simple URL based bookmark is provided with semantic and structural information by the conceptualization based on ontology. In order to deal with the dynamic usage of bookmarks, ontology learning based on a hierarchical clustering method can be exploited. As a result of our experiments, about 53.1 % of the total time was saved during collaborative browsing for seeking the equivalent set of information, compared with single Web browsing. Finally, we demonstrate implementing an application of collaborative browsing system through sharing bookmark-associated activities

User modeling for exploratory search on the Social Web. Exploiting social bookmarking systems for user model extraction, evaluation and integration

Exploratory search is an information seeking strategy that extends be- yond the query-and-response paradigm of traditional Information Retrieval models. Users browse through information to discover novel content and to learn more about the newly discovered things. Social bookmarking systems integrate well with exploratory search, because they allow one to search, browse, and filter social bookmarks. Our contribution is an exploratory tag search engine that merges social bookmarking with exploratory search. For this purpose, we have applied collaborative filtering to recommend tags to users. User models are an im- portant prerequisite for recommender systems. We have produced a method to algorithmically extract user models from folksonomies, and an evaluation method to measure the viability of these user models for exploratory search. According to our evaluation web-scale user modeling, which integrates user models from various services across the Social Web, can improve exploratory search. Within this thesis we also provide a method for user model integra- tion. Our exploratory tag search engine implements the findings of our user model extraction, evaluation, and integration methods. It facilitates ex- ploratory search on social bookmarks from Delicious and Connotea and pub- lishes extracted user models as Linked Data

Piggy Bank: Experience the Semantic Web Inside Your Web Browser

The original publication is available at www.springerlink.com http://dx.doi.org/10.1007/11574620_31The Semantic Web Initiative envisions a Web wherein information is offered free of presentation, allowing more effective exchange and mixing across web sites and across web pages. But without substantial Semantic Web content, few tools will be written to consume it; without many such tools, there is little appeal to publish Semantic Web content. To break this chicken-and-egg problem, thus enabling more flexible information access, we have created a web browser extension called Piggy Bankthat lets users make use of Semantic Web content within Web content as users browse the Web. Wherever Semantic Web content is not available, Piggy Bank can invoke screenscrapers to restructure information within web pages into Semantic Web format. Through the use of Semantic Web technologies, Piggy Bank provides direct, immediate benefits to users in their use of the existing Web. Thus, the existence of even just a few Semantic Web-enabled sites or a few scrapers already benefits users. Piggy Bank thereby offers an easy, incremental upgrade path to users without requiring a wholesale adoption of the Semantic Web’s vision. To further improve this Semantic Web experience, we have created Semantic Bank, a web server application that lets Piggy Bank users share the Semantic Web information they have collected, enabling collaborative efforts to build sophisticated Semantic Web information repositories through simple, everyday’s use of Piggy Bank

Just-in-time hypermedia

Many analytical applications, especially legacy systems, create documents and display screens in response to user queries dynamically or in real time . These documents and displays do not exist in advance, and thus hypermedia must be generated \u27just in time -automatically and dynamically. This dissertation details the idea of \u27just-in-time hypermedia and discusses challenges encountered in this research area. A fully detailed literature review about the research issues and related research work is given. A framework for the \u27just-in-time hypermedia compares virtual documents with static documents, as well as dynamic with static hypermedia functionality. Conceptual \u27just-in-time hypermedia architecture is proposed in terms of requirements and logical components. The \u27just-in-time hypermedia engine is described in terms of architecture, functional components, information flow, and implementation details. Then test results are described and evaluated. Lastly, contributions, limitations, and future work are discussed

Building and exploiting context on the web

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Proceedings of the 3rd Workshop on Social Information Retrieval for Technology-Enhanced Learning

Learning and teaching resource are available on the Web - both in terms of digital learning content and people resources (e.g. other learners, experts, tutors). They can be used to facilitate teaching and learning tasks. The remaining challenge is to develop, deploy and evaluate Social information retrieval (SIR) methods, techniques and systems that provide learners and teachers with guidance in potentially overwhelming variety of choices. The aim of the SIRTEL’09 workshop is to look onward beyond recent achievements to discuss specific topics, emerging research issues, new trends and endeavors in SIR for TEL. The workshop will bring together researchers and practitioners to present, and more importantly, to discuss the current status of research in SIR and TEL and its implications for science and teaching

A Survey of Semantic Metadata Management Models for the Social Web

12Social systems are a new generation of Web 2.0 applications, characterized by their primarily user-driven content and the ability to mediate personal and social information across communities, such as teams, communities, and organizations. The recent growth and adaptation of social systems for personal and social information management has created new opportunities for users to be producers as well as consumers of information. This paper aims at studying the different models that have been proposed to better connect resources, annotations and users and their usage in the social Web. The paper aims to answer questions like: \textit{What are the existing models that allow to semantically describe resources, users and tags in the social Web? What are the characteristics of such models? What are the differences between those models?} The final objective is to provide an understandable study and comparison of some of the existing models to help researchers, and developers, to make their decision whenever there is a need to use a semantic meta-data model in the social Web. More concretely, this work aims to be a reference guide for different professionals in order to accelerate the adoption of such technologies in the Social Web