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Private attribute inference from Facebook’s public text metadata: a case study of Korean users

Choi, Daeseon; Lee, Younho; Kim, Seokhyun; Kang, Pilsung - In: Industrial Management & Data Systems 117 (2017) 8, pp. 1687-1706

consisting of 32 attributes were collected for 111,123 Korean users. Inferences were made for four private attributes (gender … regression algorithms. Findings Experimental results showed that users’ gender can be inferred very accurately, whereas marital … available information although users are not willing to disclose them. The experimental results showed that gender, age, marital …

Persistent link: https://www.econbiz.de/10014825904

Learning about Spatial and Temporal Proximity using Tree-Based Methods

Levin, Ines - In: Statistics, Politics and Policy 13 (2022) 1, pp. 73-95

Abstract Learning about the relationship between distance to landmarks and events and phenomena of interest is a multi-faceted problem, as it may require taking into account multiple dimensions, including: spatial position of landmarks, timing of events taking place over time, and attributes of...

Persistent link: https://www.econbiz.de/10014621182

Data cleaning issues in class imbalanced datasets: instance selection and missing values imputation for one-class classifiers

Wang, Zhenyuan; Tsai, Chih-Fong; Lin, Wei-Chao - In: Data Technologies and Applications 55 (2021) 5, pp. 771-787

Purpose Class imbalance learning, which exists in many domain problem datasets, is an important research topic in data mining and machine learning. One-class classification techniques, which aim to identify anomalies as the minority class from the normal data as the majority class, are one...

Persistent link: https://www.econbiz.de/10014712610

An approach for fault prediction in SOA-based systems using machine learning techniques

Bhandari, Guru Prasad; Gupta, Ratneshwer; Upadhyay, … - In: Data Technologies and Applications 53 (2019) 4, pp. 397-421

Purpose Software fault prediction is an important concept that can be applied at an early stage of the software life cycle. Effective prediction of faults may improve the reliability and testability of software systems. As service-oriented architecture (SOA)-based systems become more and more...

Persistent link: https://www.econbiz.de/10014712641

Population estimation using Twitter for a specific space

Hara, Hiroki; Fujita, Yoshikatsu; Tsuda, Kazuhiko - In: Data Technologies and Applications 55 (2021) 3, pp. 430-445

Purpose This paper aims to estimate the population in a specific space from the numbers of posted tweets and their senders, using Twitter's real-time property and location information data. Design/methodology/approach The population to be estimated was set to be the attendance at each game among...

Persistent link: https://www.econbiz.de/10014712647

Electrocardiogram stream level correlated patterns as features to classify heartbeats for arrhythmia prediction

Al-Yarimi, Fuad Ali Mohammed; Munassar, Nabil Mohammed Ali - In: Data Technologies and Applications 54 (2020) 5, pp. 685-701

Purpose Digital computing and machine learning-driven predictive analysis in the diagnosis of non-communicable diseases are gaining significance. Globally many research studies are focusing on developing comprehensive models for such detection. Categorically in the proposed diagnosis for...

Persistent link: https://www.econbiz.de/10014712652

Between comments and repeat visit: capturing repeat visitors with a hybrid approach

Kim, Jina; Jang, Yeonju; Bae, Kunwoo; Oh, Soyoung; … - In: Data Technologies and Applications 55 (2021) 4, pp. 542-557

Purpose Understanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation...

Persistent link: https://www.econbiz.de/10014712691

Dynamic Distributed and Parallel Machine Learning algorithms for big data mining processing

Djafri, Laouni - In: Data Technologies and Applications 56 (2021) 4, pp. 558-601

Purpose This work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies. Design/methodology/approach In the age of Big Data,...

Persistent link: https://www.econbiz.de/10014712694

An algorithm to elicitate ELECTRE II, III and IV parameters

e Souza Rodrigues, Brunno; Martins Floriano, Carla; … - In: Data Technologies and Applications 55 (2020) 1, pp. 82-96

Purpose This paper presents an algorithm that can elicitate all or any combination of parameters for the ELECTRE II, III or IV, methods. The algorithm takes some steps of a machine learning ensemble technique, the random forest, and for that, the authors named the approach as Ranking Trees...

Persistent link: https://www.econbiz.de/10014712708

Predicting corporate credit rating based on qualitative information of MD&A transformed using document vectorization techniques

Choi, Jinwook; Suh, Yongmoo; Jung, Namchul - In: Data Technologies and Applications 54 (2020) 2, pp. 151-168

Purpose The purpose of this study is to investigate the effectiveness of qualitative information extracted from firm’s annual report in predicting corporate credit rating. Qualitative information represented by published reports or management interview has been known as an important source in...

Persistent link: https://www.econbiz.de/10014712720