Adnan Amin

Institute of Management Sciences, Pakistan, Peshawar · Department of Computer Sciences

This paper is about the performance of mapper, shuffle, and reduce operations on varying nature of data using different types of Hadoop’s clusters. Datasets, without duplicated and partially duplicated records were taken on single and two nodes Hadoop clusters. Experiments prove that mapper, shuffle, and reduce operations outperform on columns havi...

This study contributes to formalize a three phase customer churn prediction technique. In the first phase, a supervised feature selection procedure is adopted to select the most relevant subset of features by laying-off the redundancy and increasing the relevance that leads to reduced and highly correlated features set. In the second phase, a knowl...

Predicting the behavior of customer is at great importance for a project manager. Data driven industries such as telecommunication industries have advantage of various data mining techniques to extract meaningful information regarding customer’s future behavior. However, the prediction accuracy of these data mining techniques is significantly affec...

In the modern era of digital technology, the rapid distribution of news via social media platforms substantially contributes to the propagation of false information, presenting challenges in upholding the accuracy and reliability of information. This study presents an updated approach that utilizes Graph Neural Networks (GNNs) alongside with advanc...

As the number of IoT devices increases daily due to the rapid growth in technology, every device and network is vulnerable to attacks because it is exposed to the internet. Denial of Service (DoS) is a prevalent type of intrusion on the Internet of Things (IoT) network in which the server becomes down due to flooding requests. Distributed Denial of...

The exploration of complex networks and the arrangement of communities is a widely researched topic across various fields, reflecting research interest in a multitude of domains. Clustering algorithms have emerged as a prominent tool for community detection, gaining considerable attention in recent decades. To assess the effectiveness of clustering...

PASTIC (Pakistan Scientific Technological Information Centre)

Various models have been proposed to shed light on the evolution mechanisms of real-world complex networks (e.g., Facebook, Twitter, etc.) that can be expressed in terms of graph similarity. Generally, state-of-the-art research has assumed that complex networks in the real world are jointly driven by (i) multiplex features rather than a single pure...

Knowledge graphs (KGs) possess a vital role in enhancing the semantic comprehension of extensive datasets across many fields. It facilitate activities like recommendation systems, semantic searching, and intelligent data mining. However, lacking information can sometimes limit the usefulness of knowledge graphs (KGs), as the lack of relationships b...

Every Edge-IIoT device and network is susceptible to attacks because they are connected to the internet. The number of IoT devices grows daily due to the rapid advancement in technology. The server goes down as a result of a flood of requests in a DDoS attack, which is a common type of intrusion in the IoT. As a consequence, the business may experi...

This paper discusses the importance of feature extraction and structure similarity measurement in the analysis of complex networks. Social networks, biological systems, and transportation networks are just a few examples of the many phenomena that have been modeled using complex networks. However, analyzing these networks can be challenging due to...

The number of internet-connected devices is rising, resulting in a global network of connected devices, referred to as Internet of Things (IoT). The technologically advanced agriculture industry employs IoT to monitor their environment and automate required functionality. IoT devices generate enormous amount of confidential and critical data, hence...

Link prediction is one of the most essential and crucial tasks in complex network research since it seeks to forecast missing links in a network based on current ones. This problem has applications in a variety of scientific disciplines, including social network research, recommendation systems, and biological networks. In previous work, link predi...

Author profiling is part of information retrieval in which different perspectives of the author are observed by considering various characteristics like native language, gender, and age. Different techniques are used to extract the required information using text analysis, like author identification on social media and for Short Text Message Servic...

Online discussion forums are repositories of valuable information where users interact and articulate their ideas, opinions, and share experiences about nu merous topics. They are internet-based online communities where users can ask for help and find the solution to a problem. On online discussion forums, a new user becomes exhausted from reading...

Link prediction is a key problem in the field of undirected graph, and it can be used in a variety of contexts, including information retrieval and market analysis. By “undirected graphs”, we mean undirected complex networks in this study. The ability to predict new links in complex networks has a significant impact on society. Many complex systems...

Link prediction in a complex network is a difficult and challenging issue to address. Link prediction tries to better predict relationships, interactions and friendships based on historical knowledge of the complex network graph. Many link prediction techniques exist, including the common neighbour, Adamic-Adar, Katz and Jaccard coefficient, which...

Numerous techniques have been proposed by researchers to uncover the hidden patterns of real-world complex networks. Finding a hidden community is one of the crucial tasks for community detection in complex networks. Despite the presence of multiple methods for community detection, identification of the best performing method over different complex...

Biological network proteins are key operational particles that substantially and operationally cooperate to bring out cellular progressions. Protein links with some other biological network proteins to accomplish their purposes. Physical collaborations are commonly referred to by the relationships of domain-level. The interaction among proteins and...

Link prediction among the objects of data is one of the essential tasks in several application fields, such as spam mail detection, expert detection, information retrieval, influence detection, recommender system, surveillance of communication, and disease prediction. Link prediction aims to estimate the missing link based on the existing links in...

Link mining is an important task in the field of data mining and has numerous applications in informal community. Suppose a real-world complex network, the responsibility of this function is to anticipate those links which are not occurred yet in the given real-world network. Holding the significance of LP, the link mining or expectation job has go...

H. He, Y. Bai, E. A. Garcia, and S. Li, "ADASYN: Adaptive synthetic sampling approach for imbalanced learning." in Proc. IEEE Int. Joint Conf. Neural Networks (IJCNN'18), pp. 1322-1328, 2008

N.V. Chawla, A.Lazarevic, L.O. Hall, K. Bowyer, "SMOTEBoost: Improving Prediction of Minority Class in Boosting, Journal of Knowledge Discovery in Databases: PKDD, 2003.

1st Workshop on Leveraging customer behavior using advanced data analytics and Machine learning techniques in 9th World Conference on Information Systems and Technologies, Terceira Island, Azores, Portugal, 30-31 March to 1-2 April 2021.

Call for Papers: We invite researchers to contribute original research papers and review articles that will seek high- quality contributions regarding the recent advances in applying machine learning for solving cyberthreat for WSS challenges. Topics of interest include, but are not limited to ones listed below. * Deep learning techniques in sec...

Due to the exponential growth in technologies and a greater number of competitors in the telecom sector, the companies are facing a rigorous problem of customer churns. The customer churn is a phenomenon that highlights the customer’s intention who may switch from a certain service or even the service provider company. Many customer churn predictio...

The effective educational systems aimed at improving Cognitive Skills (CS) both in and out of institutions. Such system relies on timely prediction of CS during students’ activities in intuitions. Meanwhile, literature is saturated with the number of approaches which have used study schedules, biological and environmental factors to predict CS. How...

Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP...

The high dimensional dataset results in more noise, will require more computations, has huge sparsity linked with high dimensional features and has thus introduced great challenges in data analysis. To efficiently manipulate and address the impact of the challenges faced by high dimensional dataset, researchers used several features reduction metho...

Every year, a large volume of information about students' performance is processed in schools, colleges, and higher studies institutes. This information statistically associates students' performance with their study schedule and family-related characteristics. Recent methods have significantly contributed to student's cognitive skills (CSs) predic...

In today’s digital age, the digital transformation is necessary for almost every competitive enterprise in terms of having access to the best resources and ensuring customer satisfaction. However, due to such rewards, these enterprises are facing key concerns around the risk of next-generation data security or cybercrime which is continually increa...

To achieve excellent marks in job interviews and written examinations, a student must acquire impressive Cognitive Skills (CS) value. Nevertheless, the effects of frustration and CS Related Human Factors (CSRF) profoundly influence the student’s skills during the aforementioned cognitive tasks. The recent methods present significant student’s skill...

To achieve excellent marks in job interviews and written examinations, a student must acquire impressive Cognitive Skills (CS) value. Nevertheless, the effects of frustration and CS Related Human Factors (CSRF) profoundly influence the student’s skills during the aforementioned cognitive tasks. The recent methods present significant student’s skill...

To pass a job interview or written examination, students must have a specific set of Cognitive Skills (CS). The effects of frustration (aggression, giving up, loss of self-confidence, and depression) negatively affect these particular skills. Traditionally, a psychologist is invited for a job interview to determine these skills. Thus, there is no e...

Compromised user credential (CUC) is an activity in which someone, such as a thief, cyber-criminal or attacker gains access to your login credentials for the purpose of theft, fraud, or business disruption. It has become an alarming issue for various organizations. It is not only crucial for information technology (IT) oriented institutions using d...

Customer Churn Prediction (CCP) is a challenging activity for decision makers and machine learning community because most of the time, churn and non-churn customers have resembling features. From different experiments on customer churn and related data, it can be seen that a classifier shows different accuracy levels for different zones of a datase...

Acknowledged sgi.com and https://www.kaggle.com/becksddf/churn-in-telecoms-dataset/data website for providing dataset for researcher as publicly available.

This study exposes a serious and rapidly growing cyber threat of compromised legitimate user credentials which is very effective for cyber-criminals to gain trusted relationships with the account owners. Such a compromised user's credentials ultimately result in damage incurred by the attacker at large-scale. Moreover, the detection of compromised...

Customer churn is a critical and challenging problem affecting business and industry, in particular, the rapidly growing, highly competitive telecommunication sector. It is of substantial interest to both academic researchers and industrial practitioners, interested in forecasting the behavior of customers in order to differentiate the churn from n...

Customer retention is a major issue for various service-based organizations particularly telecom industry, wherein predictive models for observing the behavior of customers is one of the great instruments in customer retention process and inferring the future behavior of the customers. However, the performances of predictive models are greatly affe...

The rapidly rising usage of telecommunication and information networks which inter-connect modern society through computers, smart phones and other electronic devices has led to security threats and cyber-crimes (CC) activities. These cybercrime activities has ultimately resulted in CC attack classification as a serious problem in network security...

Suitable site selection for a specific purpose is a crucial activity, and of the greatest importance to a project manager. Several methods have been proposed by the research community for effective site selection, but all proposed methods incur high costs. This study explores the combination of a rough set theory approach (RSTA) with Technique for...

The Customer churn is a crucial activity in rapidly growing and mature competitive telecommunication sector and is one of the greatest importance for a project manager. Due to the high cost of acquiring new customers, customer churn prediction has emerged as an indispensable part of telecom sectors’ strategic decision making and planning process. I...

This study contributes to formalize customer churn prediction where rough set theory is used as one-class classifier and multi-class classifier to investigate the trade-off in the selection of an effective classification model for customer churn prediction. Experiments were performed to explore the performance of four different rule generation algo...