Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data ar...
Many applications in text processing require significant human effort for either labeling large document collections (when learning statistical models) or extrapolating rules from...
Due to the exponential growth of documents on the Internet and the emergent need to organize them, the automated categorization of documents into predefined labels has received an...
Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems ...
The classical (ad hoc) document retrieval problem has been traditionally approached through ranking according to heuristically developed functions (such as tf.idf or bm25) or gene...