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Publications (39)

1DOCUMENT CLASSIFICATION BY MACHINE:Theory and Practice1994  Louise Guthrie,Elbert Walkerwith the proportion of type j being Pij. We are given a random sample of size n from one of the populations, and are asked...

2A Joint Information Model for NBest Ranking2008  Patrick Pantel,Vishnu Vyasproperties extracted by our system (described below) for a random sample of two instances from a cluster of food, {apple, beef}...

3HighPerformance Tagging on Medical Texts2004  Udo Hahn,Joachim Wermterannotation was 96.7% (standard deviation: 0.6%), based on a random sample of 2000 tokens (10% of the evaluation corpus). The p...

4Open Entity Extraction from Web Search Query Logs2010  Alpa Jain,Marco Pennacchiottiexperiments we use the following datasets: Query log: A random sample of 100 million, fully anonymized queries collected by...

5Sentiment classification on customer feedback data: noisy data, large feature vectors, and the role of linguistic analysis2004  Michael Gamondealing with here are extremely noisy. Recall that on a random sample of 200 pieces of feedback even a human evaluator could...

6Genus Disambiguation: A Study in Weighted Preference1992  Rebecca Bruce,Louise Guthrieproposed sense selectien 6riteria were mn on the same random sample of 520 definitions. Table I provides a summary of the...

7Parsing with the Shortest Derivation2000  Rens Bodsubtrees larger than depth l by taking for each depth a random sample o1' 400,000 subtrecs. No subtrces larger than depth 14...

8Experiments in Automated Lexicon Building for Text Searchinglexicons fl'om the different configurations. We had chosen a random sample of 10 percent of the 2,700 words that occurred at least...

9Fine Grained Classification of Named Entities2002  Michael Fleischman,Eduard Hovygeneration is that the training set created is not a random sample of person instances in the real world. Rather, the training...

10Concept Discovery from Text2002  Dekang Lin,Patrick Pantelclustering. Buckshot first applies averagelink to a random sample of n elements to generate K clusters. It then uses...