Collaborative Personalized Top-k Processing

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As the number of scientific papers getting published is likely to soar, most of modern paper management systems (e.g. ScienceWise, Mendeley, CiteULike) support tag-based retrieval. In that, each paper is associated with a set of \emph{tags}, allowing user ...

The rapidly increasing amount of user-generated content in social tagging systems provides a huge source of information. Yet, performing effective search in these systems is very challenging, especially when we seek the most appropriate items that match a ...

The advent of online social networks created new prediction opportunities for recommender systems: instead of relying on past rating history through the use of collaborative filtering (CF), they can leverage the social relations among users as a predictor ...

Tagging in online social networks is very popular these days, as it facilitates search and retrieval of diverse resources available online. However, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes ...

Tagging in online social networks is very popular these days, as it facilitates search and retrieval of multimedia content. However, noisy and spam annotations often make it difficult to perform an efficient search. Users may make mistakes in tagging and i ...

We tackle the problem of improving the relevance of automatically selected tags in large-scale ontology-based information systems. Contrary to traditional settings where tags can be chosen arbitrarily, we focus on the problem of recommending tags (e.g., co ...

As sensors continue to proliferate, the capabilities of effectively querying not only sensor data but also its metadata becomes important in a wide range of applications. This paper demonstrates a search system that utilizes various techniques and tools fo ...

The large-scale adoption of the Web 2.0 paradigm has revolutionized the way we interact with the Web today. End-users, so far mainly passive consumers of information are now becoming active information producers, creating, uploading, and commenting on all ...

Benefiting from the advent of social software, information sharing becomes pervasive. Personalized rating systems have emerged to evaluate the quality of user-generated content in open environment and provide recommendation based on users’ past experience. ...

We consider the problem of tag prediction in collaborative tagging systems where users share and annotate resources on the Web. We put forward HAMLET, a novel approach to automatically propagate tags along the edges of a graph which relates similar documen ...

We consider the applicability of terms extracted from anchortext as a source of Web page descriptions in the form of tags. With a relatively simple and easy-to-use method, we show that anchortext significantly overlaps with tags obtained from the popular t ...

Environmental engineers from different organizations work in interdisciplinary projects having the need of information exchange. In particular, a collaborative environment with personalized access to information is needed, which supports strongly varying i ...

Collaborative Personalized Top-k Processing

Chat with Graph Search

Tag-based Paper Retrieval: Minimizing User Effort with Diversity Awareness

Personalizing Top-k Processing Online in a Peer-to-Peer Social Tagging Network

Comparing the Predictive Capability of Social and Interest Affinity for Recommendations

Spam Fighting in Social Tagging Systems

In Tags We Trust: Trust modeling in social tagging of multimedia content

Tag Recommendation for Large-Scale Ontology-Based Information Systems

Advanced Search, Visualization and Tagging of Sensor Metadata

Leveraging User-Generated Content for Information Discovery on the Web

Trust-Based Rating Prediction for Recommendation in Web 2.0 Collaborative Learning Social Software

Neighborhood-based Tag Prediction

From Web 1.0 to Web 2.0 and back - How did your Grandma use to tag?

Personalized information access in a wiki using structured tagging