Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - CAPFF
T2 - A Context-Aware Assistant for Paper Form Filling
AU - Wang, Jiangtao
AU - Wang, Yasha
AU - Wang, Yafei
PY - 2017/12
Y1 - 2017/12
N2 - This paper introduces a context-aware system, named CAPFF, for helping people in filling paper forms, mainly in two contexts: 1) people have no idea of what should be filled in certain form fields; 2) people are not aware of the mistakes they are likely to commit in entering information, which may violate data entry constraints. In the offline phase, CAPFF provides a tool to build the knowledge about a given form, and such knowledge includes instructions, field-level examples, and constraints among form fields. In the online phase, when people set out to hill a paper form, the video camera of the system determines the position of the pen and then provides assistance, based on the user's form filling context. We evaluated CAPFF's performance through 450 paper form filling activities, and the results show that the proposed CAPFF is effective in terms of both accuracy and response time.
AB - This paper introduces a context-aware system, named CAPFF, for helping people in filling paper forms, mainly in two contexts: 1) people have no idea of what should be filled in certain form fields; 2) people are not aware of the mistakes they are likely to commit in entering information, which may violate data entry constraints. In the offline phase, CAPFF provides a tool to build the knowledge about a given form, and such knowledge includes instructions, field-level examples, and constraints among form fields. In the online phase, when people set out to hill a paper form, the video camera of the system determines the position of the pen and then provides assistance, based on the user's form filling context. We evaluated CAPFF's performance through 450 paper form filling activities, and the results show that the proposed CAPFF is effective in terms of both accuracy and response time.
KW - Context-aware
KW - paper form filling
U2 - 10.1109/THMS.2016.2586487
DO - 10.1109/THMS.2016.2586487
M3 - Journal article
VL - 47
SP - 903
EP - 908
JO - IEEE Transactions on Human-Machine Systems
JF - IEEE Transactions on Human-Machine Systems
SN - 2168-2291
IS - 6
ER -