We develop a novel approach to the semantic analysis of short text segments and demonstrate its utility on a large corpus of Web search queries. Extracting meaning from short text...
A weakly supervised method uses anonymized search queries to induce a ranking among class labels extracted from unstructured text for various instances. The accuracy of the extrac...
We show that we can automatically classify semantically related phrases into 10 classes. Classification robustness is improved by training with multiple sources of evidence, inclu...
Ben Carterette, Rosie Jones, Wiley Greiner, Cory B...
A seed-based framework for textual information extraction allows for weakly supervised acquisition of open-domain class attributes over conceptual hierarchies, from a combination ...
In this work we present further development of the SpLaSH (Spoken Language Search Hawk) project. SpLaSH implements a data model for annotated speech corpora integrated with textua...