Hierarchical HMM (HHMM) parsers make promising cognitive models: while they use a bounded model of working memory and pursue incremental hypotheses in parallel, they still achieve...
Stephen Wu, Asaf Bachrach, Carlos Cardenas, Willia...
Incremental parsing techniques such as shift-reduce have gained popularity thanks to their efficiency, but there remains a major problem: the search is greedy and only explores a ...
Prior use of machine learning in genre classification used a list of labels as classification categories. However, genre classes are often organised into hierarchies, e.g., coveri...
This research explores the idea of inducing domain-specific semantic class taggers using only a domain-specific text collection and seed words. The learning process begins by indu...
As information extraction (IE) becomes more central to enterprise applications, rule-based IE engines have become increasingly important. In this paper, we describe SystemT, a rul...
Laura Chiticariu, Rajasekar Krishnamurthy, Yunyao ...