Wan Maseri Binti Wan Mohd

MaxD K-Means: A Clustering Algorithm for Auto-generation of Centroids and Distance of Data Points in Clusters

K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. The main drawback of this algorithm is that user should specify the number of cluster in advance. As an iterative clustering strategy, K-Means algorithm is very sensitive to the initial starting conditions. In this paper, we propose a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. MaxD K-means also used a novel strategy of setting the initial centroids. The experiment of the Max-D means has been conducted using synthetic data, which is taken from the Llyod’s K-Means experiments. The results from the new algorithm show that the number of iteration improves tremendously, and the number of iterations is reduced by confirming an improvement rate is up to 78%.

Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

Internet has brought a major drift in user community. Apart from its well-known usage, it also promotes social networking. Research on such social networking has advanced significantly in recent years which have been highly influenced by the online social websites. People perceive the web as a social medium that allows larger interaction among people, sharing of knowledge, or experiences. Internet or social web forums act as an agent to reproduce some general information that would benefit the users. A product review by the user is a more accurate representation of its real-world performance and web-forums are generally used to post such reviews. Though commercial review websites allow users to express their opinions in whatever way they feel, the number of reviews that a product receives could be very high. Hence, opinion mining techniques can be used to analyze the user-reviews, classify the content as positive or negative, and thereby find out how the product fares. This paper focuses its attention on providing a recommendation to the products available on the web by analyzing the context to score the sentences for each review by identifying the opinion and feature words using a novel algorithm.

A Framework of Dashboard System for Higher Education Using Graph-Based Visualization Technique

We propose a novel approach of knowledge visualization method by adopting graph-based visualization technique and incorporating Dashboard concept for higher education institutions. Two aspects are emphasized, knowledge visualization and human-machine interaction. The knowledge visualization helps users to analyze the comprehensive characteristics of the students, lecturers and subjects after the clustering process and the interaction enable domain knowledge transfer and the use of the human’s perceptual capabilities, thus increases the intelligence of the system. The knowledge visualization is enhanced through the dashboard concept where it provides significant patterns of knowledge on real-world and theoretical modeling which could be called wisdom. The framework consists of the dashboard model, system architecture and system prototype for higher education environment is presented in this paper.

Categorizing users in requirement engineering process: A case study in e-university project

In order to fulfill users requirement, it is very important to manage user effectively. Many studies have shown that most of the software project fails due to the inconsistent needs of software users with the view of software developers. Understanding user needs is not a sequential process. It involves different disciplines such as psychology, languages and communications, organizational behavior and management. This study has explored a practical approach of managing users by establishing ownership-based user groups. Each group will have its own characteristic and responsibility which will be established through policy, education and awareness program. The commitment and cooperation of each user group will be managed through identifying and managing them through cooperation based user group. The case study has been carried out in University College of Engineering & Technology Malaysia. The study has derived 4 categories of users based on ownership with its own characteristic and responsibility. As for the cooperation based user groups, it has been categorized into 4 groups. The study found that managing users through ownership-based and cooperation based user group has improved the involvement and commitment level of users during the whole software process especially during requirement engineering process.

Managing Fragmented Database Replication for Mygrants Using Binary Vote Assignment on Cloud Quorum

Replication in distributed database is the process of copying and maintaining database objects in multiple databases that make up a distributed database system. In this paper, we will manage fragmented database replication and transaction management for Malaysian Greater Research Network (MyGRANTS) using a new proposed algorithm called Binary Vote Assignment on Cloud Quorum (BVACQ). This technique will combine replication and fragmentation. Fragmentation in distributed database is very useful in terms of usage, efficiency, parallelism and also for security. This strategy will partition the database into disjoint fragments. The result shows that managing replication and transaction through proposed BVACQ able to preserve data consistency. It also increases the degrees of parallelism. This is because by using fragmentation, replication and transaction can be divided into several subqueries that operate on the fragments.

Preserving Data Replication Consistency through ROWA-MSTS

In modern distributed systems, replication receives particular awareness to provide high data availability, reliability and enhance the performance of the system. Replication becomes as significant mechanism since it enables organizations to provide users with admission to current data where and when they need it. Integrated VSFTPD with Read-One-Write-All Monitoring Synchronization Transaction System (ROWA-MSTS) has been developed to monitor data replication and transaction performs in distributed system environment. This paper presents the ROWA-MSTS framework and process flow in order to preserve the data replication consistency. The implementation shows that ROWA-MSTS able to monitor the replicated data distribution while maintaining the data consistency over multiple sites.

A knowledge-based digital dashboard for Higher Learning Institutions

We propose a novel approach of knowledge discovery method by adopting dashboard concept and incorporating elements of data clustering, visualization and knowledge codification. The dashboard was designed to help the higher institution to explore the insight of student performance by analyzing significant patterns and tacit knowledge of the experts in order to improve decision making process. The system has been developed using system development life cycle (SDLC) methodology and coded in web-based and open source environment. The dashboard architecture and software are presented in this paper.