Klaas Dellschaft

Cicero: tracking design rationale in collaborative ontology engineering

Creating and designing an ontology is a complex task requiring discussions between domain and ontology engineering experts as well as the users of an ontology. We present the Cicero tool, that facilitates efficient discussions and accelerates the convergence to decisions. Furthermore, by integrating it with an ontology editor, it helps to improve the documentation of an ontology.

Personalized search and exploration with mytag

Nowadays Web 2.0 platforms like YouTube [6], Flickr [3] and del.icio.us [2] provide large amounts of resources such as videos, photographs and social bookmarks. Common to the platforms is the classification by so called tags that can be used for organization and retrieval. A current limitation of tagging platforms is their confinement to a single media type. Furthermore, a magnitude of platforms exists for each media type. Thus, in both cases of searching resources of either the same or of different media type, a user has to search multiple platforms [7]. For example, a user needs to search on del.icio.us, RawSugar [4] and Bibsonomy [1] to find bookmarks or on Flickr and YouTube to find media related to e.g. an artist. Another limitation results from the ranking of resources as implemented by platforms such as YouTube, Flickr, and del.icio.us. Usually, the overall popularity of a resource is used for ranking search results. A personalized search is currently missing that takes the interests of a user into account. MyTag aims at solving the previously described limitations of current tagging platforms by enabling cross-media search across images, video, and social bookmarks. It offers transparent access to different single-media platforms currently including Flickr, YouTube, and del.icio.us (cf. Section 2). Furthermore, it introduces personalization features such as a personalized ranking of search results (cf. Section 3). The architecture of MyTag ensures its extensibility towards further tagging platforms (cf. Section 4).

Measuring the influence of tag recommenders on the indexing quality in tagging systems

In this paper, we investigate a methodology for measuring the influence of tag recommenders on the indexing quality in collaborative tagging systems. We propose to use the inter-resource consistency as an indicator of indexing quality. The inter-resource consistency measures the degree to which the tag vectors of indexed resources reflect how the users understand the resources. We use this methodology for evaluating how tag recommendations coming from (1) the popular tags at a resource or from (2) the users own vocabulary influence the indexing quality. We show that recommending popular tags decreases the indexing quality and that recommending the users own vocabulary increases the indexing quality.