@inproceedings{f3f602be5c3a421ebdfca57109cea5f2,
title = "Schema Integration on Massive Data Sources",
abstract = "As the fundamental phrase of collecting and analyzing data, data integration is used in many applications, such as data cleaning, bioinformatics and pattern recognition. In big data era, one of the major problems of data integration is to obtain the global schema of data sources since the global schema could be hardly derived from massive data sources directly. In this paper, we attempt to solve such schema integration problem. For different scenarios, we develop batch and incremental schema integration algorithms. We consider the representation difference of attribute names in various data sources and propose ED Join and Semantic Join algorithms to integrate attributes with different representations. Extensive experimental results demonstrate that the proposed algorithms could integrate schemas efficiently and effectively.",
keywords = "Information integration, Schema integration, Schema mapping",
author = "Tianbao Li and Haifeng Guo and Donghua Yang and Mengmeng Li and Bo Zheng and Hongzhi Wang",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.; 23rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2023 ; Conference date: 20-10-2023 Through 22-10-2023",
year = "2024",
doi = "10.1007/978-981-97-0801-7\_11",
language = "英语",
isbn = "9789819708000",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "186--206",
editor = "Zahir Tari and Keqiu Li and Hongyi Wu",
booktitle = "Algorithms and Architectures for Parallel Processing - 23rd International Conference, ICA3PP 2023, Proceedings",
address = "德国",
}