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Sarawagi, Sunita; Thomas, Shiby

doi:10.1023/a:1009887712954

Cited by 70 publications

(2 citation statements)

References 12 publications

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“…One example, is the research presented in Boulicaut, Klemettinen, and Mannila (1999), where the principle is demonstrated for association rules. Sarawagi, Thomas, and Agrawal (2000) use the same principle related to association rules and compare performances of several alternatives, by means of distinct SQL versions (SQL92 and SQL-OR). Using only basic SQL3 constructions and functions, Jamil (2004) shows that any object relational database can be mined for association rules.…”

Section: Using Standard Sqlmentioning

confidence: 99%

Extending QMBE Language with Clustering

Azevedo

Santos

2013

International Journal of Decision Support System Technology

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Business Intelligence (BI) is an important area of the Decision Support Systems (DSS) discipline. Over the past years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. This creates a gap between DM and BI systems. With the purpose of closing this gap a new DM language for BI, named as Query-Models-By-Example (QMBE), was envisaged and implemented with success, but addressing only classification rules. This paper presents an extension of QMBE language to include clustering. This represents one more step towards the integration of DM with BI, which constitutes an important issue.

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Section: Using Standard Sqlmentioning

confidence: 99%

Extending QMBE Language with Clustering

Azevedo

Santos

2013

International Journal of Decision Support System Technology

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“…The development of data mining algorithms also supports the analysis and utilization of massive data. The use of the association rule is effective for massive data processing in finding items among attributes of a large database hidden in relationships (Sarawagi et al 2000). Violations are usually related to the construction phase.…”

Section: Introductionmentioning

confidence: 99%

A real-time control approach based on intelligent video surveillance for violations by construction workers

Guo

Xiong

Gong

2018

Journal of Civil Engineering and Management

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Abstract. The unsafe behavior of workers is the main object of construction safety management, in which violations require increased attention due to their pernicious consequences. However, existing studies have merely discussed violations separately from unsafe behaviors. To respond quickly to workers' violations on site, this study proposes a real-time control approach based on intelligent video surveillance. First, scenes reflecting unsafe behaviors are automatically acquired through camera-based behavior analysis technology. Meanwhile, the time corresponding to the construction phase is recorded. Second, the temporal association rule model of worker's unsafe behavior is constructed, and the rule "construction phase→unsafe behavior" is determined by the Apriori algorithm to identify target behaviors necessary for critical control in different construction phases. Finally, statistical process control is used to find the trends of violations with frequency and mass characteristics through the dynamic monitoring of target behavior. In addition, real-time alerts of these unsafe acts are produced simultaneously. A pilot study is conducted on the cross-river tunnel project in Wuhan city, Hubei, China, and the violations related to construction machineries is proven to be controllable. Thus, the proposed approach promotes behavioral safety management on construction since it effectively controls workers' violations by real-time monitoring and analysis.

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Spatial Subgroup Discovery Applied to the Analysis of Vegetation Data

May

Ragia

2002

Practical Aspects of Knowledge Management

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Untitled

Cited by 70 publications

References 12 publications

Extending QMBE Language with Clustering

Extending QMBE Language with Clustering

A real-time control approach based on intelligent video surveillance for violations by construction workers

Spatial Subgroup Discovery Applied to the Analysis of Vegetation Data

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