@inproceedings {pub4439,
	title = {Hierarchy-aware Learning of Sequential Tool Usage via Semi-automatically Constructed Taxonomies},
	author = {Nima Nabizadeh AND Martin Ernst Heckmann AND Dorothea Kolossa},
	year = {2020},
	abstract = {While repairing a device, humans employ a series of tools that corresponds to the arrangement of the device components. Such sequences of tool usage can be learned from repair manuals, so that at each step, observing the previously applied tools, a sequential model can predict the next required tool. In this paper, we improve the tool prediction performance of such methods by additionally taking the hierarchical relationships among the tools into account. To this aim, we build a taxonomy of tools with hyponymy and hypernymy relations from the data by decomposing all multi-word expressions of the tool names. We then develop a sequential model that performs a binary prediction for each node in the taxonomy. The evaluation of the method on a dataset of repair manuals shows that encoding the tools with the constructed taxonomy and a top-down beam search for the decoding, increases the prediction accuracy and yields an interpretable taxonomy as a potentially valuable byproduct.},
	publisher = {ACL (Association for Computational Linguistics)},
	booktitle = {Joint Workshop on Multiword Expressions and Electronic Lexicons (MWE-LEX 2020) at COLING 2020 (Barcelona, Spain)},
	editor = {Stella Markantonatou, John McCrae, Jelena Mitrovi{\'c}, Carole Tiberius, Carlos Ramisch, Ashwini Vaidya, Petya Osenova, Agata Savary},
	edition = {1},
	volume = {1},
	pages = {22{\textendash}26},
	address = {online}
}