The Modern Greek Language on the Social Web: A Survey of Data Sets and Mining Applications

Nikiforos, Maria Nefeli; Voutos, Yorghos; Drougani, Anthi; Mylonas, Phivos; Kermanidis, Katia Lida

doi:10.3390/data6050052

Cited by 8 publications

(5 citation statements)

References 44 publications

(161 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…“Modularity” [ 71 ], “modular platforms” [ 72 ], “modularization” [ 73 ], or “modular islands” [ 74 ] are among the terms used. Many authors who apply text-mining approaches recognize that the presence of different suffixes is an issue [ 75 , 76 ].…”

Section: Resultsmentioning

confidence: 99%

Exploring multi-use platforms: A literature review of marine, multifunctional, modular, and mobile applications (M4s)

Xylia

Passos

Piseddu

et al. 2023

Heliyon

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Exploring multi-use platforms: A literature review of marine, multifunctional, modular, and mobile applications (M4s)

Xylia

Passos

Piseddu

et al. 2023

Heliyon

View full text Add to dashboard Cite

“…The accident investigation report is not only an important source of information for accident analysis, but also a good learning resource. Arteaga et al (2020) proposed a text mining method based on machine learning combined with GCV-LIME to determine the causal relationship of injury severity, and at the same time provide the interpretability required by traffic safety analysis (Nikiforos et al, 2021).…”

Section: Risk Factor Identification Based On Text Miningmentioning

confidence: 99%

Text mining and association rules-based analysis of 245 cement production accidents in a cement manufacturing plant

Bing

Gong

Zhou

2023

Preprint

View full text Add to dashboard Cite

Accidents such as collapse, fire, suffocation, poisoning, scalding and mechanical injuries occur frequently in cement industries. Understanding the causes of past accidents in cement companies is essential to prevent cement production accidents and reduce safety risks. However, there is currently no cause analysis of accidents that have occurred in cement companies. Hence, this paper takes cement accident cases as the basis of research, proposes a unified report analysis framework, combines data mining technology, probes deeply into the law of cement production accidents, and establishes cement accident causation analysis model to provide a basis for current safety management decisions. Firstly, 245 accident records were collected to categorize the causal factors of cement accidents in this plant according to the LDA model, and then a systematic accident causal analysis method was proposed according to the 24Model to establish a unified report analysis framework. Based on this, an improved Apriori algorithm suitable for multi-dimensional multi-layer cement enterprise accident correlation rule mining was proposed to improve the efficiency of accident mining. Using the improved Apriori algorithm, the correlation between accident causative factors and accident types as well as accident causative factors of cement enterprises was quantitatively mined, and targeted safety management suggestions were put forward.

show abstract

“…The use of modern information technology to collect, mine, and analyze data can reduce the probability of safety accidents [41]. In addition, the data mining technology can analyze the intrinsic correlation and value of the accident data in depth [58]. Text mining technology finds new information in a large amount of text data by extracting context and meaning using natural language and document processing techniques [59].…”

Section: Text Miningmentioning

confidence: 99%

Research on Safety Risk Transfer in Subway Construction Based on Text Mining and Complex Networks

Wu,

Zhang,

Huang

et al. 2023

Preprint

View full text Add to dashboard Cite

Subway construction is often in a complex natural and human-machine operating environment, and that complicated setting leads to subway construction more prone to safety accidents, which can cause substantial casualties and monetary losses. Thus, it is necessary to investigate the safety risks of subway construction. The existing literature on the identification and assessment of subway construction safety risks(SCSR) is susceptible to the influence of subjective factors. Moreover, although existing studies have explored the interrelationships between different risks, these studies usually analyze the interrelationships of single risks, lack the study of risk chain transfer relationships, and fail to find out the key path of risk transfer. Therefore, this paper innovatively combines text mining, association rules and complex networks to deep mine subway construction safety incident reports and explore risk transfer process. Firstly, it uses text mining technology to identify subway construction safety risk; Then, association rules are introduced to explore the causal relationships among safety risk; Finally, the key safety risk and important transfer paths of subway construction safety accidents (SCSA) are obtained based on the complex network model. Research results show that (a) improper safety management, unimplemented safety subject responsibilities, violation of operation rules, non-perfect safety responsibilities system and insufficient safety education and training are the key safety risk in SCSA; (b) two shorter key risk transfer paths in the subway construction safety network can be obtained: insufficient safety education and training→lower safety awareness→violation of operation rules→safety accidents; insufficient safety checks or hidden trouble investigations→violation of operation rules→safety accidents; (c) in the process of risk transfer, the risk can be controlled by controlling the key nodes or cutting off the transfer path. The results of the study provide new ideas and methods for SCSR identification and influence element mining, which help safety managers propose accurate subway construction safety risk control measures.

show abstract

The Modern Greek Language on the Social Web: A Survey of Data Sets and Mining Applications

Cited by 8 publications

References 44 publications

Exploring multi-use platforms: A literature review of marine, multifunctional, modular, and mobile applications (M4s)

Exploring multi-use platforms: A literature review of marine, multifunctional, modular, and mobile applications (M4s)

Text mining and association rules-based analysis of 245 cement production accidents in a cement manufacturing plant

Research on Safety Risk Transfer in Subway Construction Based on Text Mining and Complex Networks

Contact Info

Product

Resources

About