In this paper we describe the tag recommendation framework we developed for our social bookmark and publication sharing system BibSonomy. However, most research focused on evaluation and development of appropriate methods rather than tackling the practical challenges of how to integrate recommendation methods into real tagging systems, record and evaluate their performance. In this paper, we summarize and extend our work on different aspects of this branch of Web 2.0 research, demonstrated and evaluated within our own social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind.
History of cello and speaking tone
Therefore suitable methods that properly exploit the different dimensions of social tagging systems data are needed. In this paper, we tackle this topic from different angles: We describe data mining methods for ubiquitous and social data, specifically focusing on physical and social activities, and provide exemplary analysis results. The present work shows, how basic approaches from the field of social network analysis and information retrieval can be applied for discovering relations among names, thus extending Onomastics by data mining techniques. Abstract In social tagging systems, like Mendeley, CiteULike, and BibSonomy, users can post, tag, visit, or export scholarly publications.
booktitle = Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011), title = How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems, How Tagging Pragmatics Influence Tag Sense Discovery in Social Annotation Systems.
Proceedings of the Sixth International Semantic Web Conference, (ISWC 2007), Busan, Korea. Proceedings of the 12th International Conference on Information Visualisation (IV08), IEEE Computer Society. Integrating Tagging into the Web of Data: Overview and Combination of Existing Tag Ontologies.. It is based on data mining techniques with a level-wise approach.
In this paper, we compare citations with metrics derived from usersâ€™ activities (altmetrics) in the popular social bookmarking system BibSonomy. This enables us to classify international first names as well as ill-formed names. The assumption is that names and words influence the discoverability of a user and subsequently his/her follower count. Of particular interest is the information provided by each Twitter user’s profile page. Based on our methodology and findings, an analytics tool to improve peatland fire and haze disaster management by the Indonesian authorities is under development.
Workshop on the role of Semantic Web in Provenance Management, October 25, 2009, Semantic access to INSPIRE – How to Publish and Query Advanced GML Data.
The present work provides a comprehensive study of the intrinsic geometry of a data set, based on Gromov’s metric measure geometry and Pestov’s axiomatic approach to intrinsic dimension. Unveiling the hidden bride: deep annotation for mapping and migrating legacy data to the Semantic Web.
To this end we extend V.~Pestov’s axiomatic approach to the instrinsic dimension of data sets, based on the seminal work by M.~Gromov on concentration phenomena, and provide an adaptable and computationally feasible model for studying observable geometric invariants associated to features that are natural to both the data and the learning procedure. Geometric analysis is a very capable theory to understand the influence of the high dimensionality of the input data in machine learning (ML) and knowledge discovery (KD). Based on these objects, we propose and investigate an axiomatic approach to the intrinsic dimension of geometric data sets and establish a concrete dimension function with the desired properties.