一句话：通过领域专家用户研究评估基于语义相似度的业务流程自动补全引擎，并发现专家评分与部分NLP指标强相关。
本文关注业务流程建模中的自动化：利用已有流程知识推荐下一个待添加元素。作者回顾了一个基于业务流程语义相似度的自动补全引擎，并针对某商业产品开展领域专家用户研究，请专家对引擎给出的建议进行评分。随后将专家评分与自然语言处理领域的准确率指标进行比较。研究发现，专家评分与部分NLP指标之间存在强相关性，从而确认了该语义自动补全引擎的实用性，并总结了任何流程自动补全技术可能的改进方向。
Process modeling can benefit from automation using knowledge mined from collections of existing processes. One promising technique for such automation is the recommendation of the next elements to be added to the processes under construction. In this paper, we review an autocompletion engine that is based on the semantic similarity of business processes. To assess its efficiency in practical settings, we conduct a user study where domain experts are asked to rate the suggestions made by the engine for a commercial product. Their ratings are then compared to the engine’s accuracy measured by metrics from the natural language processing field. Our study shows a strong correlation between the expert ratings and some of these metrics. We confirm the usefulness of such an autocompletion engine, and enumerate potential improvements to any process autocompletion technique.
DOI 原文 ·
@inproceedings{paperbot6624,
title = {Evaluating Semantic Autocompletion of Business Processes with Domain Experts},
author = {Maayan Goldstein and Cecilia Gonzalez-Alvarez},
booktitle = {ASE},
year = {2021},
doi = {10.1109/ase51524.2021.9678821}
}