Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study

Recommender systems engage user profiles and appropriate filtering techniques to assist users in finding more relevant information over the large volume of information. User profiles play an important role in the success of recommendation process since they model and represent the actual user needs. However, a comprehensive literature review of recommender systems has demonstrated no concrete study on the role and impact of knowledge in user profiling and filtering approache. In this paper, we review the most prominent recommender systems in the literature and examine the impression of knowledge extracted from different sources. We then come up with this finding that semantic information from the user context has substantial impact on the performance of knowledge based recommender systems. Finally, some new clues for improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.3, August 201

Penyelesaian masalah persamaan resapan olakan satu dimensi secara selari dan berjujukan

This article discusses the solution of one-dimensional convection-diffusion equations by using Successive Over-Relaxation Red Black (SORRB) and Gauss-Seidel Red Black (GSRB) method for parallel and sequential. The implementation for this method has been performed on parallel computers for distributed memory systems using Parallel Virtual Machine (PVM) and C which used 18 personal computers with Intel Pentium IV processor. This research successfully results in affirmation of the theories presented by Foster (1995) which proposed that the percentage of efficiency decreases and the speedup factor increases when the numbers of processors are increasing. The research result also shows that the parallelization of GSRB and SORRB method is faster than sequential especially when the number ofprocessors increased. As a conclusion, problem solving by using parallelization will reduce execution time especially in solving large scale problems

Data mining approaches in business intelligence: postgraduate data analytic

Over recent years, there has been tremendous growth of interest in business intelligence (BI) for higher education. BI analysis solutions are operated to extract useful information from a multi-dimensional datasets. However, higher education-based business intelligence is complex to build, maintain and it faces the knowledge constraints. Therefore, data mining techniques provide an effective computational methods for higher educationbased business intelligence. The main purpose of using data mining approaches in business intelligence is to provide decision making solution to higher education management. This paper presents the implementation of data mining approaches in business intelligence using a total of 13508 postgraduates (PG) data. These PG data are to allow the research to identify the postgraduates who Graduate On Time (GOT) via business intelligence process integrating data mining approaches. There are four layers will be discussed in this paper: data source layer (Layer 1), data integration layer (Layer 2), logic layer (Layer 3), and reporting layer (Layer 4). The main scope of this paper is to identify suitable data mining which is to allow decision making on GOT so as to an appropriate analysis to education management on GOT. The results show that Support Vector Machine (SVM) classifier is with better accuracy of 99%. Hence, the contribution of data mining in business intelligence allows an accurate decision making in higher education

Misinterpretation on rumors towards racial conflict: a review on the impact of rumors spread during the riot of May 13, 1969

A rumor is a short-lived, unverified report, usually anonymous in its origin. Rumor exists, especially in a turbulent society. In fact, a plural society that comes from various background exhibits greater potential of its dissemination due to the diversity of aspirations and interpretations in obtaining information based from opinion differences. Malaysia had experienced the problem during the riots in Kuala Lumpur on May 13, 1969. The spread of rumors does not only affect the life victims and the destruction of the property, but also determines the path and direction of the nation’s politics. This change is in line with the prohibition of debate on sensitive matters which are enshrined in the constitution. The objective of this article is to assess the relationship between rumors and conflicts in a society. The initial discussion focuses on factors that determine the rate of spread in the society. It focuses on the authorities measures, inclusive of safety, administrative and legislative measures to control its dissemination. Finally, it focuses on the short, medium, and long-term implications arising from its dissemination. It can be concluded that the May 13 incident is an effective mechanism in controlling the conflict in the country. This does not mean that the spread of rumors specifically on negative matters will be discontinued. It relies heavily on the government’s sensitivity towards the current situation, therefore, necessary actions should be taken to address the dissemination in order to avoid similar events to recur

Analysis and Identification of Data Heterogeneity on Learning Environment Using Ontology Knowledge

Heterogeneity on learning environment is about different data and applications to support a learning process in education institutions. Distributed and various systems on learning environment is the current issues to produce big and heterogeneity data problem. A lot of relationships are formed between elements on learning environment. The element on learning environment consists of learning data, learning applications, data sources, learning concept, and data heterogeneity aspect on learning environment. These elements are interrelated and produce complex relationship between each other. A complex relationship problem between elements on learning environment makes a process of analysis and identification difficult to be done. Existing method to drawing this heterogeneity problem make confuse and misunderstanding readers. To solved this problem, researcher using ontology knowledge to describe and draw a semantic relationship that represent the complexity of data relationship on learning environment. The result of this analysis is to develop ontology knowledge to solve complexity relationship on learning environment, and also to help reader’s better understanding the complex relationship between elements on learning environment

A Concise Fuzzy Rule Base to Reason Student Performance Based on Rough-Fuzzy Approach

A fuzzy inference system employing fuzzy if then rules able to model the qualitative aspects of human expertise and reasoning processes without employing precise quantitative analyses. This is due to the fact that the problem in acquiring knowledge from human experts is that much of the information is uncertain, inconsistent, vague and incomplete (Khoo and Zhai, 2001; Tsaganou et al., 2002; San Pedro and Burstein, 2003; Yang et al., 2005). The drawbacks of FIS are that a lot of trial and error effort need to be taken into account in order to define the best fitted membership functions (Taylan and Karagözoglu, 2009) and no standard methods exist for transforming human knowledge or experience into the rule base (Jang, 1993)

Improving gender classification with feature selection in forensic anthropology

Gender classification has been one of the most vital tasks in a real world problem especially when it comes to death investigations. Developing a biological profile of an individual is a crucial step in forensic anthropology process as for the identification of gender. Forensic anthropologists employ the principle of skeleton remains to produce a biological profile. Different parts of skeleton contains different features that will contribute to gender classification. However, not all the features could contribute to gender classification and affect to a low accuracy of gender classification. Therefore, feature selection method is applied to identify the most significant features for gender classification. This paper presents the implementation of feature selection approaches which are Particle Swarm Optimization (PSO) and Harmony Search (HS) algorithm using three different dataset from Goldman Osteometric Dataset, Osteological Collection and George Murray Black Collection. All three dataset contains 4081 samples of metrics measurement and have gone through the process of classification by using Back Propagation Neural Network (BPNN) and Naïve Bayes classifier. The main scope of this paper is to identify the effect of feature selection towards gender classification. The result shows that the accuracy of gender classification for every dataset increased when feature selection is applied to the dataset. Among all the skeleton parts in this experiment, clavicle part achieved the highest increment of accuracy rate which is from 89.76% to 96.06% for PSO algorithm and 96.32% for HS

Rekabentuk sistem pemprosesan tesis secara automatik

Perpustakaan yang merupakan gedung ilmu yang penting perlu disediakan dengan kemudahan selaras dengan perkembangan ICT (Information Communication Technology). Ini adalah bertujuan untuk menggalakkan dan memudahkan orang ramai menggunakan perpustakaan. Gabungan teknologi digital dan rangkaian komunikasi ini membolehkan pengguna mengetahui koleksi sesebuah perpustakaan atau pusat sumber melalui Katalog Awam dalam talian atau OPAC (Online Public Access Catalogue) di mana sahaja mereka berada dan pada bila-bila masa. Kewujudan Katalog Awam Dalam Talian (OPAC)yang telah wujud semenjak awal tahun 80-an bukan sahaja berfungsi untuk memaklumkan kepada pengguna tentang bahan koleksi yang terdapat dalam perpustakaan malah turut menunjukkan status bahan yang dipesan tetapi belum di terima serta menyatakan bahan yang sudah dipinjam dan tarikh pemulangan. Pengguna juga boleh membuat tempahan dan membuat capaian koleksi perpustakaan lain (Ding 1998). Sistem pengurusan sumber maklumat yang lebih cekap dan baik membantu pengguna membuat capaian maklumat serta memudahkan pihak pengurusan menguruskan pusat sumber. Kemajuan teknologi ICT yang dibincangkan di atas turut di rasai oleh insitusi pengajian tinggi termasuk di pusat sumber, Fakulti Teknologi dan Sains Maklumat, Universiti Kebangsaan Malaysia

A cloud based framework for e-government implementation in developing countries

Cloud Computing technology is achieving a significant cost saving, business agility, and high scalability. However, it is a relatively new technology and its successful implementation in the governmental organizations needs careful consideration due to data sensitivity. Successful adoption of cloud-based solutions is the key for realizing the expected benefits of cloud computing technologies in the public agencies. The aim of this research is to develop a strategic framework to adopt cloud-based solutions in the public sector to improve e-government processes in developing countries. The purpose of the developed framework is to reduce the time and cost of the processes that contain interaction among governmental agencies and citizens through adopting cloud-based solutions. The framework was formulated based on the collected data analysis and the conclusions from experts' interviews. This study provides detailed guidelines to a successful launch and implementation of cloud-based solutions for e-government initiatives in the public sector