Masrah Azrifah Azmi Murad

Sentiment classification of customer reviews based on fuzzy logic

Nowadays, e-commerce is growing fast, so product reviews have grown rapidly on the web. The large number of reviews makes it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). Most existing method utilize a list of opinion words for sentiment classification. whereas, this paper propose a fuzzy logic model to perform semantic classifications of customers review into the following sub-classes: very weak, weak, moderate, very strong and strong by combinations adjective, adverb and verb to increase holistic the accuracy of lexicon approach. Fuzzy logic, unlike statistical data mining techniques, not only allows using non-numerical values also introduces the notion of linguistic variables. Using linguistic terms and variables will result in a more human oriented querying process.

Knowledge Sharing Interactions in Collaborative Software Maintenance Environment

In collaborative Software Maintenance (SM) environment, knowledge sharing is vital to ensure various parties have the necessary information to perform SM tasks. However, patterns of knowledge sharing interactions within the networked organization of SM Community of Practice (CoP) and factors that influence these interactions are yet to be established. We study the dialogues captured in the Software Configuration Management (SCM) tool used by a global SM organization and use Pajek, a Social Network Analysis (SNA) tool, to map the interactions among users and maintenance personnel. The results revealed technical, planning and domain information as most shared information. Network bottlenecks are also identified, which evolves around a key development manager, a development team leader and a systems analyst. Also, there are lack of direct interactions between programmers and domain knowledge providers. As such, the SM environment could benefit from process automations on selected tasks of the above bottleneck areas to ensure knowledge are shared across the board.

Detecting deceptive reviews using lexical and syntactic features

Deceptive opinion classification has attracted a lot of research interest due to the rapid growth of social media users. Despite the availability of a vast number of opinion features and classification techniques, review classification still remains a challenging task. In this work we applied stylometric features, i.e. lexical and syntactic, using supervised machine learning classifiers, i.e. Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO) and Naive Bayes, to detect deceptive opinion. Detecting deceptive opinion by a human reader is a difficult task because spammers try to write wise reviews, therefore it causes changes in writing style and verbal usage. Hence, considering the stylometric features help to distinguish the spammer writing style to find deceptive reviews. Experiments on an existing hotel review corpus suggest that using stylometric features is a promising approach for detecting deceptive opinions.

Security Framework of Cloud Data Storage Based on Multi Agent System Architecture: Semantic Literature Review

The purpose of this literature review is to provide the information about illustrating the usage of Multi-Agent System (MAS) techniques that can be beneficial in cloud computing platform to facilitate security of cloud data storage (CDS) among it. MAS are often distributed and agents have proactive and reactive features which are very useful for cloud data storage security (CDSS). The architecture of the system is formed from a set of agent’s communities. This paper of literature review described on the theoretical concept and approach of a security framework as well as a MAS architecture that could be implemented in cloud platform in order to facilitate security of CDS, on how the MAS technology could be utilized in a cloud platform for serving the security that is developed by using a collaborative environment of Java Agent DEvelopment (JADE). In order to facilitate the huge amount of security, our MAS architecture offered eleven security attributes generated from four main security policies of correctness, integrity, confidentially and availability of users’ data in the cloud. This paper of literature review also describes an approach that allows us to build a security cloud platform using MAS architecture and this architecture tends to use specialized autonomous agents for specific security services and allows agents to interact to facilitate security of CDS.

Adaptable Decentralized Service Oriented Architecture

In the Service Oriented Architecture (SOA), BPEL specified business processes are executed by non-scalable centralized orchestration engines. In order to address the scalability issue, decentralized orchestration engines are applied, which decentralize BPEL processes into static fragments at design time without considering runtime requirements. The fragments are then encapsulated into runtime components such as agents. There are a variety of attitudes towards workflow decentralization; however, only a few of them produce adaptable fragments with runtime environment. In this paper, producing runtime adaptable fragments is presented in two aspects. The first one is frequent-path adaptability that is equal to finding closely interrelated activities and encapsulating them in the same fragment to omit the communication cost of the activities. Another aspect is proportional-fragment adaptability, which is analogous to the proportionality of produced fragments with number of workflow engine machines. It extenuates the internal communication among the fragments on the same machine. An ever-changing runtime environment along with the mentioned adaptability aspects may result in producing a variety of process versions at runtime. Thus, an Adaptable and Decentralized Workflow Execution Framework (ADWEF) is introduced that proposes an abstraction of adaptable decentralization in the SOA orchestration layer. Furthermore, ADWEF architectures Type-1 and Type-2 are presented to support the execution of fragments created by two decentralization methods, which produce customized fragments known as Hierarchical Process Decentralization (HPD) and Hierarchical Intelligent Process Decentralization (HIPD). However, mapping the current system conditions to a suitable decentralization method is considered as future work. Evaluations of the ADWEF decentralization methods substantiate both adaptability aspects and demonstrate a range of improvements in response-time, throughput, and bandwidth-usage compared to previous methods.

Quranic-based concepts: Verse relations extraction using Manchester OWL syntax

In recent years, there is global demand for Islamic knowledge by both Muslims and non-Muslims. This has brought about number of automated applications that ease the retrieval of knowledge from the holy books. However current retrieval methods lack semantic information they are mostly base on keywords matching approach. In this paper we have proposed a Model that will make use of semantic Web technologies (ontology) to model Quran domain knowledge. The system will enhance Quran knowledge by enabling queries in natural language.

Towards New Data Access Control Technique Based on Multi Agent System Architecture for Cloud Computing

With the rise of the era of “cloud computing”, concerns about “Security” continue to increase. Cloud computing environments impose new challenges on access control techniques due to the growing scale and dynamicity of hosts within the cloud infrastructure; we proposed Multi-Agent System (MAS) architecture. This architecture consists of two agents: Cloud Service Provider Agent (CSPA) and Cloud Data Confidentiality Agent (CDConA). CSPA provides a graphical interface to the cloud user that facilitates the access to the services offered by the system. CDConA provides each cloud user by definition and enforcement expressive and flexible access structure as a logic formula over cloud data file attributes. This new access control is named as Formula-Based Cloud Data Access Control (FCDAC). A prototype of our proposed FCDAC will be designed using Prometheus Methodology and implemented using the Java Agent Development Framework Security (JADE-S).

MALIM — A new computational approach of malay morphology

Malay is categorized as an Austronesian language, a group which also contains Bahasa Indonesia and Tagalog. Quite number of morphological analyzers has been developed for Malay, including based on two-level formalism, stemming/conflation model, or even specific model. The obvious weaknesses are incompleteness and incapability of handling ambiguity which affect the accuracy of analysis. So we introduced a new technique called S-A-P-I to handle them in our analyzer — MALIM. In this paper we describe about MALIM and the empirical study to its usage. Our results proved that by using our technique increase the accuracy of morphological analysis up to 98.99% which covers 99.99% of sample data. Thus we believe this approach is the most suitable in handling morphological analysis for Malay.

Ontology semantic approach to extraction of knowledge from Holy Quran

With the continued demand for Islamic knowledge, which is mainly based on the Quran as a source of knowledge and wisdom, systems that facilitate an easy search of the content of the Quran remain a considerable challenge. Although in recent years there have been tools for Quran search, most of these tools are based on keyword search, meaning that the user needs to know the correct keywords before being able to retrieve the content of Quran. In this paper, we propose a system that supports the end user in querying and exploring the Quran ontology. The system comprises user query reformulation against the Quran ontology stored and annotated in the knowledge base. The Quran ontology c ons i s t s of n oun concepts ident i f i ed in a l - Quran, and the relationship that exists between these concepts. The user writes a query in the natural language and the proposed system reformulates the query to match the content found in the knowledge base in order to retrieve the relevant answer. The answer is represented by the Quranic verse related to the user query.

A framework of multi-agent system to facilitate security of cloud data storage

Storage in the cloud is slightly different services for slightly different needs, it’s allow users to scale storage space requirements to meet expanding requirements, improve manageability, and can be integrated easily to backup most all aspects of a businesses’ data requirements, from server to laptop. A multi-agent system (MAS) is a collection of agents that work together to achieve goal through communication and collaboration among each other. MAS are often distributed and agent has proactive and reactive features which are very useful. Cloud Computing moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. In this paper, we focus on cloud data storage security, which has always been an important aspect of quality of service. To verify the correctness, integrity, confidentially and availability of users’ data in the cloud, we propose MAS framework. Considering that the data is distributed, updated, created through different sources. This research shall be carried out in five steps that defined as A Secure Software Development Life Cycle (SecSDLC) used as a research methodology. The MAS followed the Prometheus methodology Tool (PDT) for designing section. In this paper, we consider components of MAS framework, implementing a simulation framework by using JAVA and performing an input analysis of the data and an output analysis of the simulation results.