We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
In a new model for answer retrieval, document collections are distilled offline into large repositories of facts. Each fact constitutes a potential direct answer to questions seek...
In this paper, we propose an automatic summarization system to ease web browsing for visually impaired people on handheld devices. In particular, we propose a new architecture for ...
We introduce a new dimension to the widely studied on-line approximate string matching problem, by introducing an error threshold parameter so that the algorithm is allowed to mis...