Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...
A core problem in data mining is to retrieve data in a easy and human friendly way. Automatically translating natural language questions into SQL queries would allow for the design...
We present a novel approach to recognizing Textual nt. Structural features are constructed from abstract tree descriptions, which are automatically extracted from syntactic depend...
We develop the notion of normalized information distance (NID) [7] into a kernel distance suitable for use with a Support Vector Machine classifier, and demonstrate its use for an...
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...