Informatics Research Centre

Tagging provides support for retrieval and categorization of online content depending on users' tag choice. A number of models of tagging behaviour have been proposed to identify factors that are considered to affect taggers, such as users' tagging history. In this paper, we use Semiotics Analysis and Activity theory, to study the effect the system designer has over tagging behaviour. The framework we use shows the components that comprise the tagging system and how they interact together to direct tagging behaviour. We analysed two collaborative tagging systems: CiteULike and Delicious by studying their components by applying our framework. Using datasets from both systems, we found that 35% of CiteULike users did not provide tags compared to only 0.1% of Delicious users. This was directly linked to the type of tools used by the system designer to support tagging.

This paper presents the notion of Context-based Activity Design (CoBAD) that represents context with its dynamic changes and normative activities in an interactive system design. The development of CoBAD requires an appropriate context ontology model and inference mechanisms. The incorporation of norms and information field theory into Context State Transition Model, and the implementation of new conflict resolution strategies based on the specific situation are discussed. A demonstration of CoBAD using a human agent scenario in a smart home is also presented. Finally, a method of treating conflicting norms in multiple information fields is proposed.

In this paper, we propose a context ontology model that captures context information from multiple domain applications. It consists of three fundamental classes: Extrinsic Context, Interface Context, and Intrinsic Context that corresponds to interrelated components in the activity system. The benefit of this context model is the ability to support semantic context representation and context reasoning, which can be applied to common context-based activity design. The main contribution of this paper is to introduce a notion of context-based activity design, a formal language to specify the coordination of context state transition model. This research will extend the features of JamSession by incorporating it with the semiotics theory, such as norms and information fields that governing the behaviour of human agent in particular situation

In Malaysia, floods are the natural disasters that happen every year during the monsoon season from November until January. These flood caused serious damage to houses, roads, businesses, public facilities and even killed people. Though many steps have been taken by the government in order to prevent these incidents, but it seems went unsolved. Here, the Flood Detection and Warning System (FLoWS) is proposed in helping to monitor and manage this critical situation by providing crucial information (i.e. flood conditions, plan and preparation, and many others) to the public and the local authorities at the affected area. The system is able to measure the water level and alert the public and the local authorities by sending a notification (i.e. SMS and MMS) regarding the flood conditions. Furthermore, the system enables the public and the local authorities to see the live graph data of the water level using the Android application on the mobile phone.

The proliferation 1 of optical network technology has helped to alleviate the emerging of next generation transport networks; also known as intelligent optical network. Network functions previously processed in the electrical domain have now gradually migrated to the optical domain, thus giving a huge upgrade in terms of the network capacity. However, as these networks carry a huge volume of traffic, it is imperative that the performance of these networks is measured precisely. This article analyses such a network from modeling perspective which has been developed and simulated using Omnet++ Simulation platform. The GMPLS based optical control plane has been used entirely to build such a network model.

In Malaysia, floods are the natural disasters that happen every year during the monsoon season from November until January. These flood caused serious damage to houses, roads, businesses, public facilities and even killed people. Though many steps have been taken by the government in order to prevent these incidents, but it seems went unsolved. Here, the Flood Detection and Warning System (FLoWS) is proposed in helping to monitor and manage this critical situation by providing crucial information (i.e. flood conditions, plan and preparation, and many others) to the public and the local authorities at the affected area. The system is able to measure the water level and alert the public and the local authorities by sending a notification (i.e. SMS and MMS) regarding the flood conditions. Furthermore, the system enables the public and the local authorities to see the live graph data of the water level using the Android application on the mobile phone.

Unfortunately, not many studies have been carried out to explore tacit knowledge in the area of peacekeeping operations. Therefore, this study was conducted among military observers (MILOB) to collect their tacit knowledge which can help to make decisions during situational awareness in peacekeeping operations. In order to collect the tacit knowledge, semi-structured interview sessions were conducted in a face-to-face mode. The number of respondents who participated was 20 people from various officers’ ranks in the Military Armed Forces (MAF). Therefore, this paper is aimed to explain on a methodological issue of how the tacit knowledge was investigated.

Online travel forums have become an extremely popular platform for sharing travel information, with a large number of reviews being posted daily. Travel websites such as TripAdvisor and Booking.com have turned into very important resources for hotel operators and travellers alike, for promoting hotel rooms, choosing hotels as well as for soliciting and sharing feedback. Criticisms, compliments, dissensions, etc., are now accessible anytime and anywhere on the web, and can be readily amassed, while opinion mining techniques have developed rapidly. Together they provide the opportunity and capability to analyse and deduce factors that influence travellers in their choice of hotels. In this paper, we apply opinion mining on data collected from Tripadvisor websites. In total, 11,130 reviews on 4 hotels within the four-star and five-star categories in Kuala Lumpur are crawled, collected, and mined to identify the top-k most predominant information based on the most frequent and most related terms used in describing each of the chosen hotels. The results of this study would allow travellers to see the opinions of other travellers on these hotels, and hotel operators would be able to receive feedback to improve their services and in turn promote their hotels. This study is also carried out in view of future improvements in the techniques used and the analysis performed.

With the phenomenal increase in use of Social Networking Service (SNS) and mobile technology, the consequences of cyberbullying have become an epidemic. More than 80% youth use cell phones making them extremely vulnerable to the abuse and one in three young people have been found victims of this problem. There are many different methods of detection cyberbullying behaviour patterns however rarely any focuses on analysis based on association especially in Malay language. Learning and detecting using association is a natural communication phenomenon that can help to identify abusive content from the hidden corpora, which often goes unnoticed. Association helps to identify trends, rules and patterns of the bullies and detects abusive content considering whole sets rather than focusing on single instances. The current work focuses on detection of cyberbullying instances by association analysis using the Apriori Algorithm. It mainly focuses on detecting bullying and aggressive behaviour on Twitter. Over 80 different patterns with high confidence levels were detected that can be successfully implemented for the detection process. The high confidence levels are indicative of the efficiency of association analysis for cyberbully detection in SNS.

Tacit knowledge tends to be an invaluable knowledge repository in lifelong learning. Critical domains such as military learning cannot solely rely on traditional manuals and methods due to the unforeseen and uncertain scenarios brought about by advances in modern warfare methods and technology. There is essential knowledge hidden in experiential learning that is very difficult to formalise but critical to be incorporated and taught. The current work aims to extract the relationships between lesson learnt from experiences and current basic military survival skills training among a group of officer cadets using the framework of document and keyword relationship analysis (FDKRA). Finally, the relationships are presented using various visualisation techniques, including word cloud, network graph and bubble graph. The research reveals the existence of important knowledge, not contained otherwise in formal documentation, and thus, highlighting the need to examine and generate a tacit knowledge corpus especially in critical domains.