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With the growing importance of customer service in contemporary business, recognizing the intents behind service dialogues has become essential for the strategic success of enterprises. However, the nature of dialogue data varies significantly across different scenarios, and implementing an intent parser for a specific domain often involves tedious feature engineering and a heavy workload of data labeling. In this paper, we propose a novel Neural-Bayesian Program Learning model named Dialogue-Intent Parser (DI-Parser), which specializes in intent parsing under data-hungry settings and offers promising performance improvements. DI-Parser effectively utilizes data from multiple sources in a "Learning to Learn" manner and harnesses the "wisdom of the crowd" through few-shot learning capabilities on human-annotated datasets. Experimental results demonstrate that DI-Parser outperforms state-of-the-art deep learning models and offers practical advantages for industrial-scale applications.

General Intelligence, was held March 6-9 in Arlington, Virginia. Pascal Hitzler chaired the program committee. The first day of the conference featured in-depth tutorials on leading AGI systems and approaches, including introductions to the SOAR, Texai, and OpenCog software, and overviews of the logic-based, reinforcement learning and program-induction approaches to AGI. Following this, the main conference on Saturday and Sunday featured a number of themed sessions: Evaluation and Metrics (chaired by John Laird), Robotics and Embodiment (chaired by Itamar Arel), Cognitive Architectures (chaired by Pei Wang and Stephen Reed), Logical Approaches to AGI (chaired by Selmer Bringsjord), Learning and Reasoning (chaired by Selmer Bringsjord), Speech and Language (chaired by Moshe Looks), and Self-Awareness and Consciousness (chaired by Ben Goertzel). There were fewer industry participants because in early 2009 (due to the global economic crisis) many U.S. firms were restricting On the other hand there was an Emanuel Kitzelmann, Martin Hofmann, and Ute even greater international participation, including Schmid, from the Cognitive Systems Group at the a keynote speech by Juergen Schmidhuber (from University of Bamberg, who work in the AI tradition IDSIA, in Lugano, Switzerland, and the Technical of "inductive programing." Their paper University of Munich) and a large number of presentations described a clever way to reformulate the conclusions from German researchers.