In this paper we describe an empirical study of human-human multi-tasking dialogues (MTD), where people perform multiple verbal tasks overlapped in time. We examined how conversan...
We examine 89 websites from federal regulatory agencies in order to evaluate their ease of use for those interested in commenting on or learning about their proposed regulations. ...
The class imbalance problem (when one of the classes has much less samples than the others) is of great importance in machine learning, because it corresponds to many critical app...
The quality of large-scale recommendation systems has been insufficient in terms of the accuracy of prediction. One of the major reasons is caused by the sparsity of the samples, ...
Semantic hashing[1] seeks compact binary codes of data-points so that the Hamming distance between codewords correlates with semantic similarity. In this paper, we show that the p...