Introduction to algorithms
Unresolved issues in paragraph planning
Current research in natural language generation
Getting the message across in RST-based text generation
Current research in natural language generation
Building natural language generation systems
Building natural language generation systems
SPoT: a trainable sentence planner
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Capturing the interaction between aggregation and text planning in two generation systems
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semantic role labeling via integer linear programming inference
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Collective content selection for concept-to-text generation
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Beyond the pipeline: discrete optimization in NLP
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
ACM Transactions on Speech and Language Processing (TSLP)
Bounding and comparing methods for correlation clustering beyond ILP
ILP '09 Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing
Transliteration as constrained optimization
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning and inference with constraints
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Global inference for sentence compression an integer linear programming approach
Journal of Artificial Intelligence Research
Discourse constraints for document compression
Computational Linguistics
Semi-supervised semantic role labeling via structural alignment
Computational Linguistics
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Generating natural language descriptions from OWL ontologies: the natural OWL system
Journal of Artificial Intelligence Research
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The role of aggregation in natural language generation is to combine two or more linguistic structures into a single sentence. The task is crucial for generating concise and readable texts. We present an efficient algorithm for automatically learning aggregation rules from a text and its related database. The algorithm treats aggregation as a set partitioning problem and uses a global inference procedure to find an optimal solution. Our experiments show that this approach yields substantial improvements over a clustering-based model which relies exclusively on local information.