Personalized Questions, Answers and Grammars: Aiding the Search for Relevant Web Information

Marta Gatius


Abstract
This work proposes an organization of knowledge to facilitate the generation of personalized questions, answers and grammars from web documents. To reduce the human effort needed in the generation of the linguistic resources for a new domain, the general aspects that can be reuse across domains are separated from those more specific. The proposed approach is based on the representation of the main domain concepts as a set of attributes. These attributes are related to a syntactico-semantic taxonomy representing the general relationships between conceptual and linguistic knowledge. User models are incorporated by distinguishing different user groups and relating each group to the appropriate conceptual attributes. Then, the data is extracted from the web documents and represented as instances of the domain concepts. Questions, answers and grammars are generated from these instances.
Anthology ID:
W17-3530
Volume:
Proceedings of the 10th International Conference on Natural Language Generation
Month:
September
Year:
2017
Address:
Santiago de Compostela, Spain
Venues:
INLG | WS
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
203–207
Language:
URL:
https://www.aclweb.org/anthology/W17-3530
DOI:
10.18653/v1/W17-3530
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PDF:
http://aclanthology.lst.uni-saarland.de/W17-3530.pdf