Creating, updating, and aggregating web contents from different web users and sites form the heart idea of web2.0. However, web users originate from different communities, and follow their own semantics (referred to ...
详细信息
Creating, updating, and aggregating web contents from different web users and sites form the heart idea of web2.0. However, web users originate from different communities, and follow their own semantics (referred to as local contexts in this paper) to represent and interpret web contents. Therefore, several discrepancies could rise up between the semantics of web authors and readers. In this paper, we present several web2.0 use cases, and illustrate the possible challenges and trends to handle the local contexts of web users in these use cases.
Video content recommenders are becoming wide spread in the age of ubiquitous access to the internet and web2.0. But how does the context of video consumption effect content preference? This paper argues for a greater...
详细信息
Video content recommenders are becoming wide spread in the age of ubiquitous access to the internet and web2.0. But how does the context of video consumption effect content preference? This paper argues for a greater understanding of the impact of viewing context upon preference adaptation in the new age of multi platform, mobile video entertainment. This paper advocates an approach which investigates preference adaptation from the perspective of users self moderating content choices in response to perceptions of the current viewing context. The author suggests ethnographic study of naturalistic content consumption behaviours as a possible methodology to uncover insight into this area, which could inform design requirements for future video recommenders operating in cross context environments.
With this paper we tie in with what we presented during last year's workshop [5] where we illustrated how to analyze users' tagging and rating behavior to construct user- and context models that can be used to...
详细信息
With this paper we tie in with what we presented during last year's workshop [5] where we illustrated how to analyze users' tagging and rating behavior to construct user- and context models that can be used to perform adaptations and to issue recommendations in order to create more user-tailored web Portals. This time we want to present more sophisticated tagging paradigms and their influence on users collaboration behavior and the construction of user- and context-models. The concepts presented are currently been prototypically implemented within IBM's webSphere Portal and can be presented in a live demo at the workshop.
web server logs have been used via techniques such as user profiling and recommendation systems to improve user experience on websites. The data contained within server logs however has generally been inaccessible to ...
详细信息
web server logs have been used via techniques such as user profiling and recommendation systems to improve user experience on websites. The data contained within server logs however has generally been inaccessible to nontechnical stakeholders on website development projects due to the terminology and presentation used. We describe a process that uses visualisation to enable these stakeholders to identify questions about site usage including user profiling and behaviour. The development of this tool utilising web2.0 technologies is described as well as feedback from the first stage of user evaluation on a real-world multi-national web development project called e-Bug. The potential for this process to elicit user attributes and behaviour that can be incorporated into automated user profiling systems is also discussed.
This article investigates several well-known social network applications such as ***, Flickr and identifies social data portability as one of the main technical issues that need to be addressed in the future. We argue...
详细信息
This article investigates several well-known social network applications such as ***, Flickr and identifies social data portability as one of the main technical issues that need to be addressed in the future. We argue that this issue can be addressed by building social networks as Semantic webapplications with FOAF, SIOC, and Linked Data technologies, and prove it by implementing a prototype application using Java and core Semantic web standards. Furthermore, the developed prototype shows how features from semantic websites such as Freebase and DBpedia can be reused in social applications and lead to more relevant content and stronger social connections.
Exploiting the rich traces of users' web interaction promises to enable cross-application user modeling techniques, which is in particular interesting for applications that have a small user population or that are...
详细信息
Exploiting the rich traces of users' web interaction promises to enable cross-application user modeling techniques, which is in particular interesting for applications that have a small user population or that are used infrequently. In this paper we present a framework for the effective interchange of user profiles. In addition to derivation rules for user profile reasoning, the framework employs flexible mash-ups of RSS-based user data streams for combining heterogeneous user data in a web2.0 environment.
Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for fin...
详细信息
Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. In this paper, we present a tag-based recommender system which suggests similar web pages based on the similarity of their tags from a web2.0 tagging application. The proposed approach extends the basic similarity calculus with external factors such as tag popularity, tag representativeness and the affinity between user and tag. In order to study and evaluate the recommender system, we have conducted an experiment involving 38 people from 12 countries using data from ***, a social bookmarking web system on which users can share their personal bookmarks.
The goal of this paper is to report our experiences from integrating item-based collaborative filtering into the web2.0 site ***. We discuss the necessary steps to implement the selected Slope One algorithm in our re...
详细信息
The goal of this paper is to report our experiences from integrating item-based collaborative filtering into the web2.0 site ***. We discuss the necessary steps to implement the selected Slope One algorithm in our real world application. It was necessary to conduct performance optimization to allow for recommendations without any delays in page generation on our site. Firstly, we significantly reduced the data model by including only items similarities for pairs of items where both items been rated by at least k users. Secondly, we precomputed recommended items for users. By analyzing the empirical results, we found out that user activity increased on the site after introducing the recommender. In addition, users rated recommended videos higher on average than others which indicates that the recommender allowed users to find preferred videos more effectively.
Authoring support for semantic annotations represent the wiki way of the Semantic web, ultimately leading to the wiki version of the Semantic web's eternal dilemma: why should authors correctly annotate their cont...
详细信息
Authoring support for semantic annotations represent the wiki way of the Semantic web, ultimately leading to the wiki version of the Semantic web's eternal dilemma: why should authors correctly annotate their content? The obvious solution is to make the ratio between the needed effort and the acquired advantages as small as possible. Two are, at least, the specificities that set wikis apart from other web-accessible content in this respect: social aspects (wikis are often the expression of a community) and technical issues (wikis are edited "on-line"). Being related to a community, wikis are intrinsically associated to the model of knowledge of that community, making the relation between wiki content and ontologies the result of a natural process. Being edited on-line, wikis can benefit from a synergy of web technologies that support all the information sharing process, from authoring to delivery. In this paper we present an approach to reduce the authoring effort by providing ontology-based tools to integrate models of knowledge with authoring-support technologies, using a functional approach to content fragment creation that plays nicely with the "wiki way" of managing information.
E-recruitment is one of the most successful e-business applications supporting both, headhunters and job seekers. The explosive growth of online job offers makes the usage of information extraction techniques to build...
详细信息
E-recruitment is one of the most successful e-business applications supporting both, headhunters and job seekers. The explosive growth of online job offers makes the usage of information extraction techniques to build up, e.g., job portals in a semi-automatic way a necessity. Existing approaches, however, hardly cope with the heterogeneous and semi-structured nature of job offers nor do they consider potentials offered by web2.0 technologies. This paper proposes an information extraction system called "JobOlize"1, realized for arbitrarily structured IT job offers. To improve extraction quality, a hybrid approach is employed, combining existing NLP-techniques with a new form of context-driven extraction, incorporating layout, structure and content information. To allow users a proper adaptation of the extraction results while preserving the look and feel of the original web pages, a rich client interface is provided. The improvements in extraction quality are justified on basis of a case study and the experiences gained are generalized and critically reflected by discussing lessons learned.
暂无评论