EMNLP
2004
14 years 28 days ago
2004
Most statistical parsers have used the grammar induction approach, in which a stochastic grammar is induced from a treebank. An alternative approach is to induce a controller for ...
EMNLP
2004
14 years 28 days ago
2004
In this paper, we introduce TextRank
EMNLP
2004
14 years 28 days ago
2004
If two translation systems differ differ in performance on a test set, can we trust that this indicates a difference in true system quality? To answer this question, we describe b...
EMNLP
2004
14 years 28 days ago
2004
Given a parallel parsed corpus, statistical treeto-tree alignment attempts to match nodes in the syntactic trees for a given sentence in two languages. We train a probabilistic tr...
EMNLP
2004
14 years 28 days ago
2004
Starting from first principles, we re-visit the statistical approach and study two forms of the Bayes decision rule: the common rule for minimizing the number of string errors and...
EMNLP
2004
14 years 28 days ago
2004
State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translat...
EMNLP
2004
14 years 28 days ago
2004
This paper proposes a novel method to compile statistical models for machine translation to achieve efficient decoding. In our method, each statistical submodel is represented by ...
EMNLP
2004
14 years 28 days ago
2004
This work applies boosted wrapper induction (BWI), a machine learning algorithm for information extraction from semi-structured documents, to the problem of named entity recogniti...
EMNLP
2004
14 years 28 days ago
2004
This paper presents Japanese morphological analysis based on conditional random fields (CRFs). Previous work in CRFs assumed that observation sequence (word) boundaries were fixed...
EMNLP
2004
14 years 28 days ago
2004
Anticipating the availability of large questionanswer datasets, we propose a principled, datadriven Instance-Based approach to Question Answering. Most question answering systems ...