The heterogeneity of Web information services poses new problems in the processing of user queries over distributed federated data. It was recerntly proven that the query translation between two information services supporting all Boolean operators can be done in an optimal way. On the Web, however, the situation when at least one Boolean operator is not supported is frequent. We study the case where a Boolean user query cannot be directly translated and should be split into sub-queries. We propose two strategies for query subsumption and discuss in detail the strategy which minimizes the number of submitted sub-queries. We derive an appropriate query form for the minimal strategy and demonstrate how both translation strategies are implemented in the Knowledge Brokers system.
Query Translation for Distributed Information Gathering on the Web
| Boris Chidlovskii, Uwe Borghoff |
| Proc. of the Int'l Database Engineering and Applications Symposium, July, 1998, UK |
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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