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Article
Publication date: 4 December 2018

Zhongyi Hu, Raymond Chiong, Ilung Pranata, Yukun Bao and Yuqing Lin

Malicious web domain identification is of significant importance to the security protection of internet users. With online credibility and performance data, the purpose of this…

Abstract

Purpose

Malicious web domain identification is of significant importance to the security protection of internet users. With online credibility and performance data, the purpose of this paper to investigate the use of machine learning techniques for malicious web domain identification by considering the class imbalance issue (i.e. there are more benign web domains than malicious ones).

Design/methodology/approach

The authors propose an integrated resampling approach to handle class imbalance by combining the synthetic minority oversampling technique (SMOTE) and particle swarm optimisation (PSO), a population-based meta-heuristic algorithm. The authors use the SMOTE for oversampling and PSO for undersampling.

Findings

By applying eight well-known machine learning classifiers, the proposed integrated resampling approach is comprehensively examined using several imbalanced web domain data sets with different imbalance ratios. Compared to five other well-known resampling approaches, experimental results confirm that the proposed approach is highly effective.

Practical implications

This study not only inspires the practical use of online credibility and performance data for identifying malicious web domains but also provides an effective resampling approach for handling the class imbalance issue in the area of malicious web domain identification.

Originality/value

Online credibility and performance data are applied to build malicious web domain identification models using machine learning techniques. An integrated resampling approach is proposed to address the class imbalance issue. The performance of the proposed approach is confirmed based on real-world data sets with different imbalance ratios.

Article
Publication date: 27 November 2020

Chaoqun Wang, Zhongyi Hu, Raymond Chiong, Yukun Bao and Jiang Wu

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of…

Abstract

Purpose

The aim of this study is to propose an efficient rule extraction and integration approach for identifying phishing websites. The proposed approach can elucidate patterns of phishing websites and identify them accurately.

Design/methodology/approach

Hyperlink indicators along with URL-based features are used to build the identification model. In the proposed approach, very simple rules are first extracted based on individual features to provide meaningful and easy-to-understand rules. Then, the F-measure score is used to select high-quality rules for identifying phishing websites. To construct a reliable and promising phishing website identification model, the selected rules are integrated using a simple neural network model.

Findings

Experiments conducted using self-collected and benchmark data sets show that the proposed approach outperforms 16 commonly used classifiers (including seven non–rule-based and four rule-based classifiers as well as five deep learning models) in terms of interpretability and identification performance.

Originality/value

Investigating patterns of phishing websites based on hyperlink indicators using the efficient rule-based approach is innovative. It is not only helpful for identifying phishing websites, but also beneficial for extracting simple and understandable rules.

Details

The Electronic Library , vol. 38 no. 5/6
Type: Research Article
ISSN: 0264-0473

Keywords

Content available
Article
Publication date: 11 April 2022

Zhongyi Hu, Yukun Bao and Wu Jiang

365

Abstract

Details

Journal of Systems and Information Technology, vol. 24 no. 2
Type: Research Article
ISSN: 1328-7265

Article
Publication date: 6 February 2017

Zhongyi Wang, Jin Zhang and Jing Huang

Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as news feed…

Abstract

Purpose

Current segmentation systems almost invariably focus on linear segmentation and can only divide text into linear sequences of segments. This suits cohesive text such as news feed but not coherent texts such as documents of a digital library which have hierarchical structures. To overcome the focus on linear segmentation in document segmentation and to realize the purpose of hierarchical segmentation for a digital library’s structured resources, this paper aimed to propose a new multi-granularity hierarchical topic-based segmentation system (MHTSS) to decide section breaks.

Design/methodology/approach

MHTSS adopts up-down segmentation strategy to divide a structured, digital library document into a document segmentation tree. Specifically, it works in a three-stage process, such as document parsing, coarse segmentation based on document access structures and fine-grained segmentation based on lexical cohesion.

Findings

This paper analyzed limitations of document segmentation methods for the structured, digital library resources. Authors found that the combination of document access structures and lexical cohesion techniques should complement each other and allow for a better segmentation of structured, digital library resources. Based on this finding, this paper proposed the MHTSS for the structured, digital library resources. To evaluate it, MHTSS was compared to the TT and C99 algorithms on real-world digital library corpora. Through comparison, it was found that the MHTSS achieves top overall performance.

Practical implications

With MHTSS, digital library users can get their relevant information directly in segments instead of receiving the whole document. This will improve retrieval performance as well as dramatically reduce information overload.

Originality/value

This paper proposed MHTSS for the structured, digital library resources, which combines the document access structures and lexical cohesion techniques to decide section breaks. With this system, end-users can access a document by sections through a document structure tree.

Article
Publication date: 6 June 2016

Lixin Xia, Zhongyi Wang, Chen Chen and Shanshan Zhai

Opinion mining (OM), also known as “sentiment classification”, which aims to discover common patterns of user opinions from their textual statements automatically or…

Abstract

Purpose

Opinion mining (OM), also known as “sentiment classification”, which aims to discover common patterns of user opinions from their textual statements automatically or semi-automatically, is not only useful for customers, but also for manufacturers. However, because of the complexity of natural language, there are still some problems, such as domain dependence of sentiment words, extraction of implicit features and others. The purpose of this paper is to propose an OM method based on topic maps to solve these problems.

Design/methodology/approach

Domain-specific knowledge is key to solve problems in feature-based OM. On the one hand, topic maps, as an ontology framework, are composed of topics, associations, occurrences and scopes, and can represent a class of knowledge representation schemes. On the other hand, compared with ontology, topic maps have many advantages. Thus, it is better to integrate domain-specific knowledge into OM based on topic maps. This method can make full use of the semantic relationships among feature words and sentiment words.

Findings

In feature-level OM, most of the existing research associate product features and opinions by their explicit co-occurrence, or use syntax parsing to judge the modification relationship between opinion words and product features within a review unit. They are mostly based on the structure of language units without considering domain knowledge. Only few methods based on ontology incorporate domain knowledge into feature-based OM, but they only use the “is-a” relation between concepts. Therefore, this paper proposes feature-based OM using topic maps. The experimental results revealed that this method can improve the accuracy of the OM. The findings of this study not only advance the state of OM research but also shed light on future research directions.

Research limitations/implications

To demonstrate the “feature-based OM using topic maps” applications, this work implements a prototype that helps users to find their new washing machines.

Originality/value

This paper presents a new method of feature-based OM using topic maps, which can integrate domain-specific knowledge into feature-based OM effectively. This method can improve the accuracy of the OM greatly. The proposed method can be applied across various application domains, such as e-commerce and e-government.

Details

The Electronic Library, vol. 34 no. 3
Type: Research Article
ISSN: 0264-0473

Keywords

Article
Publication date: 15 June 2012

Jie Huang

After Ma Yingjeou's re‐election in 2012, Mainland China and Taiwan will continue cooperation in economic fields. The purpose of this paper is to undertake research on a bilateral…

Abstract

Purpose

After Ma Yingjeou's re‐election in 2012, Mainland China and Taiwan will continue cooperation in economic fields. The purpose of this paper is to undertake research on a bilateral investment agreement (BIA) between Mainland China and Taiwan.

Design/methodology/approach

The paper uses statistics to demonstrate the growing cross‐strait investment and incompetent contemporary investment protection mechanisms in Mainland China and Taiwan. The paper also compares laws in Mainland China and Taiwan and the investment protection agreements concluded by Mainland and Taiwan with other countries, respectively.

Findings

Based on the similarities of current laws and the investment protection agreements concluded by Mainland China and Taiwan with other countries, respectively, Mainland China and Taiwan can possibility agree upon major provisions of a BIA. Solutions are provided to both macro and micro challenges against a successful BIA.

Research limitations/implications

It is hard to predict whether the BIA will promote political integration between Mainland China and Taiwan in the near future.

Practical implications

A BIA can boost investors' confidence.

Social implications

This paper may serve as a humble reference for both the Mainland China and Taiwan government when negotiating the BIA.

Originality/value

Cross‐strait investment is an important and prosperous field in practice, but has not been fully explored in literature thus far. This Article aims to fill this gap.

Details

Journal of Chinese Economic and Foreign Trade Studies, vol. 5 no. 2
Type: Research Article
ISSN: 1754-4408

Keywords

Article
Publication date: 19 December 2023

Yanzhe Liu, Minrui Guo, Zhongyi Han, Beata Gavurova, Stefano Bresciani and Tao Wang

This study aims to investigate the impact of digital orientation (DO) on organizational resilience (OR) and explore the contingency effects of human resource slack and nature of…

Abstract

Purpose

This study aims to investigate the impact of digital orientation (DO) on organizational resilience (OR) and explore the contingency effects of human resource slack and nature of enterprise ownership.

Design/methodology/approach

The model hypotheses were tested using fixed effects regression on panel data collected from Chinese A-share listed manufacturing firms spanning from 2007 to 2020.

Findings

DO has a positive effect on OR. Human resource slack positively moderates the relationship between DO and OR. Additionally, DO enhances OR more effectively in non-state-owned firms than in state-owned firms.

Research limitations/implications

This study relies on data from a single industry from a single country.

Practical implications

The study supports that firms facing uncertainty, risk and pressure should promptly develop their DO strategy. Firms can derive greater resilience from implementing a DO strategy when they have a high-level human resource pool. State-owned enterprises will benefit from a DO strategy if they make some adaptive changes in leadership, structure, culture and mindset aspects.

Originality/value

This study is the first to examine the relationship between DO and OR, contributing to the existing literature on digital transformation and organizational resilience. It offers valuable insights for practitioners and policymakers seeking to adapt their organizations for the digital era and foster predictive, defensive and growth responses strategies in a dynamic business environment.

Details

Journal of Manufacturing Technology Management, vol. 35 no. 2
Type: Research Article
ISSN: 1741-038X

Keywords

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