We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
In this paper we propose a novel document retrieval model in which text queries are augmented with multi-dimensional taxonomy restrictions. These restrictions may be relaxed at a ...
Marcus Fontoura, Vanja Josifovski, Ravi Kumar, Chr...
A taxonomy organizes concepts or topics in a hierarchical structure and can be created manually or via automated systems. A major drawback of taxonomies is that they require users...
Xiaoguang Qi, Dawei Yin, Zhenzhen Xue, Brian D. Da...
A typical collection of personal information contains many documents and mentions many concepts (e.g., person names, events, etc.). In this environment, associative browsing betwe...
Jinyoung Kim, Anton Bakalov, David A. Smith, W. Br...
In this paper, we present the main features of VISTO (Vector Image Serach TOol), a new Content-Based Image Retrieval (CBIR) system for vector images. Though unsuitable for photore...
Tania Di Mascio, Daniele Frigioni, Laura Tarantino