TY - GEN
T1 - Automatic Form Filling with Form-BERT
AU - Fuchs, Gilad
AU - Roitman, Haggai
AU - Mandelbrod, Matan
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/7/11
Y1 - 2021/7/11
N2 - Digital-forms are commonly used for collecting structured information from users. However, filling digital-forms that include a large number of fields is tedious and error-prone. Auto-filling form fields for the user is highly beneficial for improving user experience and potentially collecting more valuable information (in cases where not all fields are mandatory). Online E-commerce marketplaces quite often utilize such forms to collect listing attributes from sellers. In this work, we describe Form-BERT - a Transformer-based model which is optimized for auto-filling listing attributes given the following inputs: free-text, list of known attribute names, and zero or more attribute values. Form-BERT can be further used iteratively to leverage filled out attributes as the form filling progresses.
AB - Digital-forms are commonly used for collecting structured information from users. However, filling digital-forms that include a large number of fields is tedious and error-prone. Auto-filling form fields for the user is highly beneficial for improving user experience and potentially collecting more valuable information (in cases where not all fields are mandatory). Online E-commerce marketplaces quite often utilize such forms to collect listing attributes from sellers. In this work, we describe Form-BERT - a Transformer-based model which is optimized for auto-filling listing attributes given the following inputs: free-text, list of known attribute names, and zero or more attribute values. Form-BERT can be further used iteratively to leverage filled out attributes as the form filling progresses.
KW - deep-learning
KW - natural language processing
KW - transformers
UR - https://www.scopus.com/pages/publications/85111701581
U2 - 10.1145/3404835.3463063
DO - 10.1145/3404835.3463063
M3 - Conference contribution
AN - SCOPUS:85111701581
T3 - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
SP - 1850
EP - 1854
BT - SIGIR 2021 - Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval
PB - Association for Computing Machinery, Inc
T2 - 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2021
Y2 - 11 July 2021 through 15 July 2021
ER -