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"first": "Judith", |
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"abstract": "A renaissance of interest in corpus-based statistical methods has rekindled old controversies-rationalist vs. empiricist philosophies, theory-driven vs. data-driven methodologies, symbolic vs. statistical techniques. The aim of this workshop was to set aside a priori biases and explore the balancing act that must take place when symbolic and statistical approaches are brought together. We received an impressive number of high quality submissions, indicating the level of interest in these questions. Papers were accepted from authors having a wide range of perspectives in order to initiate discussion that includes philosophical, theoretical, and practical issues. Research of this kind requires that the researcher make choices: What knowledge will be represented symbolically and how will it be obtained? What assumptions underlie the statistical model? What is the researcher gaining by combining approaches? Questions like these, and the metaphor of the balancing act, provide a unifying theme to these contributions from a wide spectrum of language researchers. We wish to thank all those who submitted papers for consideration. We also acknowledge several anonymous reviewers who helped to make the program stronger. Finally, we particularly thank the authors who prepared their submissions under a very tight timetable.", |
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"text": "A renaissance of interest in corpus-based statistical methods has rekindled old controversies-rationalist vs. empiricist philosophies, theory-driven vs. data-driven methodologies, symbolic vs. statistical techniques. The aim of this workshop was to set aside a priori biases and explore the balancing act that must take place when symbolic and statistical approaches are brought together. We received an impressive number of high quality submissions, indicating the level of interest in these questions. Papers were accepted from authors having a wide range of perspectives in order to initiate discussion that includes philosophical, theoretical, and practical issues. Research of this kind requires that the researcher make choices: What knowledge will be represented symbolically and how will it be obtained? What assumptions underlie the statistical model? What is the researcher gaining by combining approaches? Questions like these, and the metaphor of the balancing act, provide a unifying theme to these contributions from a wide spectrum of language researchers. We wish to thank all those who submitted papers for consideration. We also acknowledge several anonymous reviewers who helped to make the program stronger. Finally, we particularly thank the authors who prepared their submissions under a very tight timetable.", |
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