Large scare semi-supervised pattern recognition and data mining from images and text

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Large scale pattern recognition and data mining techniques have resulted in broad and tangible impacts on applications ranging from improved general purpose internet search and semi-automated internet portal construction to accelerated discovery in bioinformatics. Many problems in pattern recognition and data mining arise in a setting where it is easy to obtain a small amount of labeled training data relative to the amount of available unlabeled data. Semi-supervised methods for pattern recognition allow labeled data to be combined with unlabeled data to improve the results of a recognition system. Information extraction is a type of data mining that seeks to extract structured database records from unstructured data. Once information is extracted it is possible to use the underlying structured representation for a variety of tasks such as enhancing search or subsequent data analysis. The research proposed here will develop new general purpose semi-supervised information extraction techniques. There is also a growing interest in addressing problems in pattern recognition and data mining can benefit from a tighter coupling of computer vision and text processing techniques. Concrete examples include: internet scale image search, object recognition with thousands of potential categories and the extraction of information from both images and text descriptions of biological experiments; however, many other emerging problems have similar properties. The research in this proposal thus also aims to develop principled and efficient methods for semi-supervised pattern recognition, data mining and information extraction with an emphasis on problems that involve the simultaneous processing of images and text. While the emphasis of this work will be on general purpose algorithms and techniques, to develop and evaluate techniques we propose to use the concrete scenarios of creating an extremely large scale visual encyclopedia by mining the web and creating algorithms also tailored to the more specialized settings of biological image and text analysis. Research will result in training highly qualified personnel in the development of techniques appropriate for internet scale and genome scale processing - skills in high demand.