Data Technologies and Applications

Mining the determinants of review helpfulness: a novel approach using intelligent feature engineering and explainable AI

Jiho Kim, Hanjun Lee, Hongchul Lee

This paper aims to find determinants that can predict the helpfulness of online customer reviews (OCRs) with a novel approach.

A hybrid approach for predicting missing follower–followee links in social networks using topological features with ensemble learning

Riju Bhattacharya, Naresh Kumar Nagwani, Sarsij Tripathi

Social networking platforms are increasingly using the Follower Link Prediction tool in an effort to expand the number of their users. It facilitates the discovery of…

A cascaded deep-learning-based model for face mask detection

Akhil Kumar

This work aims to present a deep learning model for face mask detection in surveillance environments such as automatic teller machines (ATMs), banks, etc. to identify…

Construction of public security indicators based on characteristics of shared group behavior patterns

XiYue Deng, Xiaoming Li, Zhenzhen Chen, Mengli Zhu, Naixue Xiong, Li Shen

Human group behavior is the driving force behind many complex social and economic phenomena. Few studies have integrated multi-dimensional travel patterns and city…

Analyzing the structure of tourism destination network based on digital footprints: taking Guilin, China as a case

Caihua Yu, Tonghui Lian, Hongbao Geng, Sixin Li

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to…

A boosting-based transfer learning method to address absolute-rarity in skin lesion datasets and prevent weight-drift for melanoma detection

Lokesh Singh, Rekh Ram Janghel, Satya Prakash Sahu

Automated skin lesion analysis plays a vital role in early detection. Having relatively small-sized imbalanced skin lesion datasets impedes learning and dominates research…

A collaborative trend prediction method using the crowdsourced wisdom of web search engines

Ze-Han Fang, Chien Chin Chen

The purpose of this paper is to propose a novel collaborative trend prediction method to estimate the status of trending topics by crowdsourcing the wisdom in web search…

A deep neural networks-based fusion model for COVID-19 rumor detection from online social media

Heng-yang Lu, Jun Yang, Wei Fang, Xiaoning Song, Chongjun Wang

The COVID-19 has become a global pandemic, which has caused large number of deaths and huge economic losses. These losses are not only caused by the virus but also by the…

Hybrid data analytic technique for grading fairness

Thepparit Banditwattanawong, Arnon Marco Polo Jankasem, Masawee Masdisornchote

Fair grading produces learning ability levels that are understandable and acceptable to both learners and instructors. Norm-referenced grading can be achieved by several…

Utility optimization-based multi-stakeholder personalized recommendation system

Rahul Shrivastava, Dilip Singh Sisodia, Naresh Kumar Nagwani

In a multi-stakeholder recommender system (MSRS), stakeholders are the multiple entities (consumer, producer, system, etc.) benefited by the generated recommendations…

Credit default swap prediction based on generative adversarial networks

Shu-Ying Lin, Duen-Ren Liu, Hsien-Pin Huang

Financial price forecast issues are always a concern of investors. However, the financial applications based on machine learning methods mainly focus on stock market…

An Argentine ant system algorithm for partial set covering problem

Xiaofan Liu, Yupeng Zhou, Minghao Yin, Shuai Lv

The paper aims to provide an efficient meta-heuristic algorithm to solve the partial set covering problem (PSCP). With rich application scenarios, the PSCP is a…

Privacy-preserving techniques in recommender systems: state-of-the-art review and future research agenda

Dhanya Pramod

This study explores privacy challenges in recommender systems (RSs) and how they have leveraged privacy-preserving technology for risk mitigation. The study also…

Feature distillation and accumulated selection for automated fraudulent publisher classification from user click data of online advertising

Deepti Sisodia, Dilip Singh Sisodia

The problem of choosing the utmost useful features from hundreds of features from time-series user click data arises in online advertising toward fraudulent publisher's…

Ranking the ontology development methodologies using the weighted decision matrix

Prashant Kumar Sinha, Biswanath Dutta, Udaya Varadarajan

The current work provides a framework for the ranking of ontology development methodologies (ODMs).

Social recruiting: an application of social network analysis for preselection of candidates

Stevan Milovanović, Zorica Bogdanović, Aleksandra Labus, Marijana Despotović-Zrakić, Svetlana Mitrović

The paper aims to studiy social recruiting for finding suitable candidates on social networks. The main goal is to develop a methodological approach that would enable…

Techniques to detect terrorists/extremists on the dark web: a review

Hanan Alghamdi, Ali Selamat

With the proliferation of terrorist/extremist websites on the World Wide Web, it has become progressively more crucial to detect and analyze the content on these websites…

Modular framework for similarity-based dataset discovery using external knowledge

Martin Nečaský, Petr Škoda, David Bernhauer, Jakub Klímek, Tomáš Skopal

Semantic retrieval and discovery of datasets published as open data remains a challenging task. The datasets inherently originate in the globally distributed web jungle…

Text mining the mission statements of the most ethical companies

Tuncay Bayrak

This paper explores and examines the mission statements of the most ethical companies across the globe in terms of their main purposes, values, goals, and objective, and…

Exploring the effectiveness of word embedding based deep learning model for improving email classification

Deepak Suresh Asudani, Naresh Kumar Nagwani, Pradeep Singh

Classifying emails as ham or spam based on their content is essential. Determining the semantic and syntactic meaning of words and putting them in a high-dimensional…

Artificial intelligence technologies for more flexible recommendation in uniforms

Chih-Hao Wen, Chih-Chan Cheng, Yuh-Chuan Shih

This research aims to collect human body variables via 2D images captured by digital cameras. Based on those human variables, the forecast and recommendation of the…

3MO-AHP: an inconsistency reduction approach through mono-, multi- or many-objective quality measures

Carla Martins Floriano, Valdecy Pereira, Brunno e Souza Rodrigues

Although the multi-criteria technique analytic hierarchy process (AHP) has successfully been applied in many areas, either selecting or ranking alternatives or to derive…

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

Laouni Djafri

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…