The tremendous growth of information on the Internet has been above our ability to process. A recommender system, which filters out useful information and generate recommendations, has been introduced to help users overcome the information overload problem and has been widely applied in an ever-increasing number of e-commercial websites. Collaborative filtering and content-based recommendation methods are two major approaches used in recommender systems. The collaborative filtering predicts items which a particular user prefers by using a database about the past preferences of users with similar interests. The content-based method analyses the content of the objects to generate a representative list of the user’s interests, and then compares the similarity of item descriptions. These two methods have some drawbacks in dealing with situations such as sparse data and cold start problems. Recently, hybrid methods combining collaborative filtering and content-based methods have been proposed to overcome these limitations. However, personalized recommender system attempt to penetrate people’s various demand and generate the tailored recommendations. A highly effective and personalised recommender system may still face new challenges including interestdrifting and multicriteria optimisation. For example, a user’s interest may change over time. They may no longer like a item which was strongly preferred. Another example is that a person’s preference is varying and always has multiple criteria. Classic collaborative filtering uses a single overall rating for prediction. It does not properly reflect the opinion on a item and the reason why people rated this item high or low. Unfortunately, the current recommender systems do not consider these important factors. First, we proposed a novel hybrid recommender system to overcome interest-drifting by embedding the time-sensitive functions into the recommendation process. The experimental results show that the intergraded approach with interest-drifting can constantly perform better and provide users with higher quality recommendations. Meanwhile, the experimental results on different size of training dataset show that our algorithm can boost the prediction accuracy for all configurations. The contributions of this proposed algorithm are in two main aspects. First, using time function to reflect users’ intersts changing in order to achieve higher quality of recommendations. Second, using intergraded methods to solve some problems such as sparsity and cold start. Then we developed a new technique to aggregate the multicriteria ratings for predicting more accurate recommendations. The results show that our algorithms outperforms the traditional collaborative filtering recommender system on both accuracy of predicting ratings and accuracy of recommendations. The one of contributions in this proposed method is that we introduced the multicriteria concept into recommender systems to reflect the users’ opinion more accurate. Another contribution is that we develop a linear method to aggregate multicriteria to single rating for higher quality of recommendations. Our experiments demonstrate that the recommendation achieved better performances when interest-drifting and multicriteria ratings were considered. The significance of our research study is that we consider incorporating interest-drifting, and multicriteria ratings into a recommender system to generate personalised and effective recommendations.

Online banking systems have become more common and widely used in daily life, bringing huge changes in modern banking transaction activities and giving us a greater opportunity to access the banking system anytime and anywhere. At the same time, however, one of the key challenges that still remain is to fully resolve the security concerns associated with the online banking system. Many clients feel that online banking is not secure enough, and to increase its security levels, many banks simply add more identity-checking steps or put on more security measures to some extent to give users the impression of a secure online banking system. However, this is easier to be said than done, because we believe that more identity-checking steps could compromise the usability of the online banking system, which is an inevitable feature in design of usable and useful online banking systems. Banks can simply enhance their security level with more sophisticated technologies, but this does not seem to guarantee the online banking system is in line with its key usability concern. Therefore, the research question raised in this thesis is to establish the relationships between usability, security and trustworthiness in the online banking system. To demonstrate these relationships, three experiments were carried out using the simulation of an online banking logon procedure to provide a similar online banking experience. Post questionnaires were used to measure the three concepts, i.e. usability, security and trustworthiness. The resulting analyses revealed that simply adding more identity-checking steps in the online banking system did not improve the customers? perceived security and trustworthiness, nor the biometric security technique (i.e., fingerprints) did enhance the subjective ratings on the perceived security and trustworthiness. This showed that the systems designer needs to be aware that the customer?s perception of the online banking system is not the same as that conceived from a technical standpoint.

This research found that Geospatial Information Systems (GIS) or spatial mapping provides the potential for significantly improving asset management flexibility. Space relates everything to everything else so spatial relationships can replace technically constructed relationships found in typical databases. This means that the effort associated with database re-design in the face of change is significantly reduced, or removed.

Māori have entered a period of development that, more than ever before, requires them to explore complex options and make careful decisions about the way forward. This complexity stems from three particular areas. First, from having essentially two sets of rights, as New Zealanders and as Māori, and being active in the struggle to retain those rights. Second, from trying to define and determine development pathways that are consistent with their traditional Māori values, and which align with their desire to participate in and enjoy a modern New Zealand and a global society. Third, from attempting development within a political and societal environment that is governed by a different and dominant culture. Māori, historically and contemporarily, have a culture that leads them to very different views of the world and development pathways than pakeha New Zealanders (D. Marsden, 1994, p. 697). Despite concerted effort and mis placed belief the Māori world view has survived and is being adopted by Māori youth. The Māori worldview sometimes collides with the view of the governing pakeha culture of New Zealand, which values rights, assets and behaviours differently. Despite these differences and the complexities it remains important to measure progress and inform debate about best practice and future options. In this regard, statistical information is crucial, and is generally recognised as one of the currencies of development (World Summit of the Information Society, 2003). Māori increasingly desire to measure and be informed about the feasibility and progress of their development choices in a way that is relevant to their values and culture. Where a Māori view of reality is not present there is a high risk that decisions and actions will reflect a different worldview, will fail to deal with cultural complexities, and ultimately will not deliver the intended development outcomes.