一句话：提出 ExpCheck，基于格式与语义相似度自动识别电子表格中的可扩展组，F1 达 73.1%。
电子表格用户常通过重复相似的单元格块（unit）来组织数据与计算，一个 unit 及其扩展出的连续单元构成可扩展组。可扩展组共享相同或相似的格式与语义，是电子表格中的基本结构，但现有电子表格系统并不识别它，导致数据集成、错误检测等分析工具无法利用该结构进行精确分析。本文提出 ExpCheck 自动提取可扩展组：其观察是连续的、格式与语义相似的 unit 很可能属于同一可扩展组，因此检查每个单元格的格式及其对应语义，再按相似度将其分类到可扩展组。作者在 EUSES 和 VEnron 语料库中随机抽样的 120 个电子表格上评估 ExpCheck，实验表明其有效，F1-measure 达 73.1%，显著优于现有最佳技术（13.3%）。
Spreadsheets are widely used in various business tasks. Spreadsheet users may put similar data and computations by repeating a block of cells (a unit) in their spreadsheets. We name the unit and all its expanding ones as an expandable group. All units in an expandable group share the same or similar formats and semantics. As a data storage and management tool, expandable groups represent the fundamental structure in spreadsheets. However, existing spreadsheet systems do not recognize any expandable groups. Therefore, other spreadsheet analysis tools, e.g., data integration and fault detection, cannot utilize this structure of expandable groups to perform precise analysis. In this paper, we propose ExpCheck to automatically extract expandable groups in spreadsheets. We observe that continuous units that share the similar formats and semantics are likely to be an expandable group. Inspired by this, we inspect the format of each cell and its corresponding semantics, and further classify them into expandable groups according to their similarity. We evaluate ExpCheck on 120 spreadsheets randomly sampled from the EUSES and VEnron corpora. The experimental results show that ExpCheck is effective. ExpCheck successfully detect expandable groups with F1-measure of 73.1%, significantly outperforming the state-of-the-art techniques (F1-measure of 13.3%).
DOI 原文 ·
@inproceedings{paperbot4742,
title = {Expandable group identification in spreadsheets},
author = {Wensheng Dou and Shi Han and Liang Xu and Dongmei Zhang and Jun Wei},
booktitle = {ASE},
year = {2018},
doi = {10.1145/3238147.3238222}
}