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ACL
2003
13 years 5 months ago
Unsupervised Learning of Arabic Stemming Using a Parallel Corpus
This paper presents an unsupervised learning approach to building a non-English (Arabic) stemmer. The stemming model is based on statistical machine translation and it uses an Eng...
Monica Rogati, J. Scott McCarley, Yiming Yang
ACL
2003
13 years 5 months ago
Evaluation Challenges in Large-Scale Document Summarization
We present a large-scale meta evaluation of eight evaluation measures for both single-document and multi-document summarizers. To this end we built a corpus consisting of (a) 100 ...
Dragomir R. Radev, Simone Teufel, Horacio Saggion,...
ACL
2003
13 years 5 months ago
A Tabulation-Based Parsing Method that Reduces Copying
This paper presents a new bottom-up chart parsing algorithm for Prolog along with a compilation procedure that reduces the amount of copying at run-time to a constant number (2) p...
Gerald Penn, Cosmin Munteanu
ACL
2003
13 years 5 months ago
Text Chunking by Combining Hand-Crafted Rules and Memory-Based Learning
This paper proposes a hybrid of handcrafted rules and a machine learning method for chunking Korean. In the partially free word-order languages such as Korean and Japanese, a smal...
Seong-Bae Park, Byoung-Tak Zhang
ACL
2003
13 years 5 months ago
Constructing Semantic Space Models from Parsed Corpora
Traditional vector-based models use word co-occurrence counts from large corpora to represent lexical meaning. In this paper we present a novel approach for constructing semantic ...
Sebastian Padó, Mirella Lapata
ACL
2003
13 years 5 months ago
Towards a Model of Face-to-Face Grounding
We investigate the verbal and nonverbal means for grounding, and propose a design for embodied conversational agents that relies on both kinds of signals to establish common groun...
Yukiko I. Nakano, Gabe Reinstein, Tom Stocky, Just...
ACL
2003
13 years 5 months ago
Minimum Error Rate Training in Statistical Machine Translation
Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is on...
Franz Josef Och
ACL
2003
13 years 5 months ago
Syntactic Features and Word Similarity for Supervised Metonymy Resolution
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Malvina Nissim, Katja Markert
ACL
2003
13 years 5 months ago
Exploiting Parallel Texts for Word Sense Disambiguation: An Empirical Study
A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automati...
Hwee Tou Ng, Bin Wang, Yee Seng Chan