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For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract values of well-motivated features of utterances, such as speaker direction, punctuation marks, and a new feature, called dialogue act cues, which we find to be more effective than cue(More)
We present an empirical investigation of various ways to automatically identify phrases in a tagged corpus that are useful for dialogue act tagging. We found that a new method (which measures a phrase's deviation from an optimally-predictive phrase), enhanced with a lexical filtering mechanism, produces significantly better cues than manually-selected cue(More)
We are researching the interaction between the rule and the ontology layers of the Semantic Web, by comparing two options: 1) using OWL and its rule extension SWRL to develop an integrated ontology/rule language, and 2) layering rules on top of an ontology with RuleML and OWL. Toward this end, we are developing the SWORIER system, which enables efficient(More)
We have determined the complete nucleotide sequence of human cellular c-myc, which is homologous to the transforming gene, v-myc, of myelocytomatosis virus MC29. Analysis of the genetic information and alignment with the known sequence of chicken c-myc and v-myc indicates: (i) An intervening sequence can be identified by consensus splice signals. The unique(More)
To interpret natural language at the discourse level, it is very useful to accurately recognize dialogue acts, such as SUGGEST, in identifying speaker intentions. Our research explores the utility of a machine learning method called Transformation-Based Learning (TBL) in computing dialogue acts, because TBL has a number of advantages over alternative(More)
Nef is a membrane-associated cytoplasmic phosphoprotein that is well conserved among the different human (HIV-1 and HIV-2) and simian immunodeficiency viruses and has important roles in down-regulating the CD4 receptor and modulating T-cell signaling pathways. The ability to modulate T-cell signaling pathways suggests that Nef may physically interact with(More)
We introduce a significant improvement for a relatively new machine learning method called Transformation-Based Learning. By applying a Monte Carlo strategy to randomly sample from the space of rules, rather than exhaustively analyzing all possible rules, we drastically reduce the memory and time costs of the algorithm, without compromising accuracy on(More)
We have examined human T-lymphotropic virus type I (HTLV-I) gene expression in the human T-cell line, C8166-45 (C81), as a model to define the gene products expressed from defective proviruses. C81 cells contain one complete and two different deleted proviral genomes. The internal deletions of the latter encompass most of the gag to env region. All three(More)
Human T-lymphocytic cell line H9 infected with the HTLV-IIIB isolate of human immunodeficiency virus type 1 (HIV-1) synthesizes two forms of the Nef protein (p25 and p27) that differ both in molecular weight and charge. Different subpopulations of viruses were isolated from the HTLV-IIIB stock which induce expression of only p25 or p27. Cells infected with(More)
The oncogenes coding for the Harvey murine sarcoma virus p21ras protein as well as those coding for myc, myb, and mht products were fused to the amino-terminal portion of the bacteriophage lambda cII gene on the expression vector pJL6. In addition two regions of the gene for the human T-cell leukemia virus subgroup I (HTLV-I) envelope were expressed in our(More)