Advances in databases and information systems. ADBIS最新文献

GASP: Graph-based Approximate Sequential Pattern Mining for Electronic Health Records. 基于图的电子健康记录近似顺序模式挖掘。

Advances in databases and information systems. ADBIS Pub Date : 2021-08-01 Epub Date: 2021-07-17 DOI: 10.1007/978-3-030-85082-1_5

Wenqin Dong, Eric W Lee, Vicki Stover Hertzberg, Roy L Simpson, Joyce C Ho

{"title":"GASP: Graph-based Approximate Sequential Pattern Mining for Electronic Health Records.","authors":"Wenqin Dong, Eric W Lee, Vicki Stover Hertzberg, Roy L Simpson, Joyce C Ho","doi":"10.1007/978-3-030-85082-1_5","DOIUrl":"https://doi.org/10.1007/978-3-030-85082-1_5","url":null,"abstract":"Sequential pattern mining can be used to extract meaningful sequences from electronic health records. However, conventional sequential pattern mining algorithms that discover all frequent sequential patterns can incur a high computational and be susceptible to noise in the observations. Approximate sequential pattern mining techniques have been introduced to address these shortcomings yet, existing approximate methods fail to reflect the true frequent sequential patterns or only target single-item event sequences. Multi-item event sequences are prominent in healthcare as a patient can have multiple interventions for a single visit. To alleviate these issues, we propose GASP, a graph-based approximate sequential pattern mining, that discovers frequent patterns for multi-item event sequences. Our approach compresses the sequential information into a concise graph structure which has computational benefits. The empirical results on two healthcare datasets suggest that GASP outperforms existing approximate models by improving recoverability and extracts better predictive patterns.","PeriodicalId":93244,"journal":{"name":"Advances in databases and information systems. ADBIS","volume":"1450 ","pages":"50-60"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485653/pdf/nihms-1712842.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39483619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

SMAT: An attention-based deep learning solution to the automation of schema matching. SMAT:一种基于注意力的模式匹配自动化深度学习解决方案。

Advances in databases and information systems. ADBIS Pub Date : 2021-08-01 Epub Date: 2021-08-16 DOI: 10.1007/978-3-030-82472-3_19

Jing Zhang, Bonggun Shin, Jinho D Choi, Joyce C Ho

{"title":"SMAT: An attention-based deep learning solution to the automation of schema matching.","authors":"Jing Zhang, Bonggun Shin, Jinho D Choi, Joyce C Ho","doi":"10.1007/978-3-030-82472-3_19","DOIUrl":"https://doi.org/10.1007/978-3-030-82472-3_19","url":null,"abstract":"Schema matching aims to identify the correspondences among attributes of database schemas. It is frequently considered as the most challenging and decisive stage existing in many contemporary web semantics and database systems. Low-quality algorithmic matchers fail to provide improvement while manually annotation consumes extensive human efforts. Further complications arise from data privacy in certain domains such as healthcare, where only schema-level matching should be used to prevent data leakage. For this problem, we propose SMAT, a new deep learning model based on state-of-the-art natural language processing techniques to obtain semantic mappings between source and target schemas using only the attribute name and description. SMAT avoids directly encoding domain knowledge about the source and target systems, which allows it to be more easily deployed across different sites. We also introduce a new benchmark dataset, OMAP, based on real-world schema-level mappings from the healthcare domain. Our extensive evaluation of various benchmark datasets demonstrates the potential of SMAT to help automate schema-level matching tasks.","PeriodicalId":93244,"journal":{"name":"Advances in databases and information systems. ADBIS","volume":"12843 ","pages":"260-274"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8487677/pdf/nihms-1722415.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39485849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Correction to: An Efficient Index for Reachability Queries in Public Transport Networks 修正:公共交通网络中可达性查询的有效索引

Advances in databases and information systems. ADBIS Pub Date : 2020-08-17 DOI: 10.1007/978-3-030-54832-2_17

Bezaye Tesfaye, Nikolaus Augsten, Mateusz Pawlik, Michael H. Böhlen, Christian S. Jensen

引用次数: 1

An Efficient Index for Reachability Queries in Public Transport Networks 公交网络可达性查询的高效索引

Advances in databases and information systems. ADBIS Pub Date : 2020-07-08 DOI: 10.1007/978-3-030-54832-2_5

Bezaye Tesfaye, Nikolaus Augsten, Mateusz Pawlik, Michael H. Böhlen, Christian S. Jensen

引用次数: 1

Databases and Information Systems: 14th International Baltic Conference, DB&IS 2020, Tallinn, Estonia, June 16–19, 2020, Proceedings 数据库和信息系统:第14届波罗的海国际会议，DB&IS 2020，爱沙尼亚塔林，2020年6月16日至19日，论文集

Advances in databases and information systems. ADBIS Pub Date : 2020-01-01 DOI: 10.1007/978-3-030-57672-1

引用次数: 1

Advances in Databases and Information Systems: 23rd European Conference, ADBIS 2019, Bled, Slovenia, September 8–11, 2019, Proceedings 数据库和信息系统进展:第23届欧洲会议，ADBIS 2019，斯洛文尼亚，布莱德，2019年9月8-11日，会议录

Advances in databases and information systems. ADBIS Pub Date : 2019-01-01 DOI: 10.1007/978-3-030-28730-6

T. Welzer

引用次数: 2

Advances in Databases and Information Systems: Third East European Conference, ADBIS’99 Maribor, Slovenia, September 13–16, 1999 Proceedings 数据库和信息系统的进展:第三届东欧会议，ADBIS ' 99 Maribor，斯洛文尼亚，1999年9月13-16日

Advances in databases and information systems. ADBIS Pub Date : 1900-01-01 DOI: 10.1007/3-540-48252-0

Ladjel Bellatreche, P. Valduriez, Tadeuz Morzy

引用次数: 2

Advances in Databases and Information Systems: 26th European Conference, ADBIS 2022, Turin, Italy, September 5–8, 2022, Proceedings 数据库和信息系统进展:第26届欧洲会议，ADBIS 2022，意大利都灵，2022年9月5日至8日，会议录

Advances in databases and information systems. ADBIS Pub Date : 1900-01-01 DOI: 10.1007/978-3-031-15740-0

引用次数: 0