We propose a new hierarchical generative model for textual data, where words may be generated by topic specific distributions at any level in the hierarchy. This model is naturally well suited to clustering documents in preset or automatically generated hierarchies, as well as categorising new documents in an existing hierarchy. Training algorithms are derived for both cases and illustrated on real data by clustering news stories and categorising newsgroup messages. Finally, the generated model may be used to derive a Fisher kernel expressing similarity between documents.
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A Hierarchical Model for Clustering and Categorising Documents
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| Eric Gaussier, Cyril Goutte, Kris Popat, Francine Chen |
| Advances in Information Retrieval -- Proceedings of the 24th BCS-IRSG European Colloquium on IR Research (ECIR-02), Glasgow, March 25-27, 2002. Lecture Notes in Computer Science 2291, pp. 229-247, Springer. |
VISION
The research we conduct on expressive visual representations is applicable to visual search, object detection, image classification and the automatic extraction of 3D human poses and shapes that can be used for human behavior understanding and prediction, human-robot interaction or even avatar animation. We also extract 3D information from images that can be used for intelligent robot navigation, augmented reality and the 3D reconstruction of objects, buildings or even entire cities.
Our work covers the spectrum from unsupervised to supervised approaches, and from very deep architectures to very compact ones. We’re excited about the promise of big data to bring big performance gains to our algorithms but also passionate about the challenge of working in data-scarce and low-power scenarios.
Furthermore, we believe that a modern computer vision system needs to be able to continuously adapt itself to its environment and to improve itself via lifelong learning. Our driving goal is to use our research to deliver embodied intelligence to our users in robotics, autonomous driving, via phone cameras and any other visual means to reach people wherever they may be.
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