As part of a large effort to acquire large repositories of facts from unstructured text on the Web, a seed-based framework for textual information extraction allows for weakly sup...
This work presents a study to bridge topic modeling and personalized search. A probabilistic topic model is used to extract topics from user search history. These topics can be se...
We present a lightweight framework for processing uncertain emergent knowledge that comes from multiple resources with varying relevance. The framework is essentially RDF-compatibl...
— We consider the problem of finding the relevant named entities in response to a search query over a given text corpus. Entity search can readily be used to augment conventiona...
A weakly-supervised extraction method identifies concepts within conceptual hierarchies, at the appropriate level of specificity (e.g., Bank vs. Institution), to which attribute...