Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

Standing on the shoulders of ants : stigmergy in the Web

Stigmergy is a biological term used when discussing insect or swarm behaviour, and describes a model supporting environmental communication separately from artefacts or agents. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, or similarly termites and their termite mound building process. What is interesting with this mechanism is that highly organized societies are achieved with a lack of any apparent management structure. Stigmergic behavior is implicit in the Web where the volume of users provides a self-organizing and self-contextualization of content in sites which facilitate collaboration. However, the majority of content is generated by a minority of the Web participants. A significant contribution from this research would be to create a model of Web stigmergy, identifying virtual pheromones and their importance in the collaborative process. This paper explores how exploiting stigmergy has the potential of providing a valuable mechanism for identifying and analyzing online user behavior recording actionable knowledge otherwise lost in the existing web interaction dynamics. Ultimately this might assist our building better collaborative Web sites.

Exploration and optimization of user experience in viewing videos on a mobile phone

Compared with viewing videos on PCs or TVs, mobile users have different experiences in viewing videos on a mobile phone due to different device features such as screen size and distinct usage contexts. To understand how mobile user’s viewing experience is impacted, we conducted a field user study with 42 participants in two typical usage contexts using a custom-designed iPhone application. With user’s acceptance of mobile video quality as the index, the study addresses four influence aspects of user experiences, including context, content type, encoding parameters and user profiles. Accompanying the quantitative method (acceptance assessment), we used a qualitative interview method to obtain a deeper understanding of a user’s assessment criteria and to support the quantitative results from a user’s perspective. Based on the results from data analysis, we advocate two user-driven strategies to adaptively provide an acceptable quality and to predict a good user experience, respectively. There are two main contributions from this paper. Firstly, the field user study allows a consideration of more influencing factors into the research on user experience of mobile video. And these influences are further demonstrated by user’s opinions. Secondly, the proposed strategies — user-driven acceptance threshold adaptation and user experience prediction — will be valuable in mobile video delivery for optimizing user experience.

Towards the biofortification of banana fruit for enhanced micronutrient content

In Uganda, vitamin A deficiency (VAD) and iron deficiency anaemia (IDA) are major public health problems with between 15-32% of children under 5 years of age showing VAD and 73% being anaemic. This is largely due to the fact that the staple food crop of the country, banana, is low in pro-vitamin A and iron, therefore leading to dietary deficiencies. Although worldwide progress has been made to control VAD and IDA through supplementation, food fortification and diet diversification, their long term sustainability and impact in developing countries such as Uganda is limited. The approach taken by researchers at Queensland University of Technology (QUT), Australia, in collaboration with the National Agricultural Research Organization (NARO), Uganda, to address this problem, is to generate consumer acceptable banana varieties with significantly increased levels of pro-vitamin A and iron in the fruit using genetic engineering techniques. Such an approach requires the use of suitable, well characterised genes and promoters for targeted transgene expression. Recently, a new banana phytoene synthase gene (APsy2a) involved in the synthesis of pro-vitamin A (pVA) carotenoids was isolated from a high â-carotene banana (F’ei cv Asupina). In addition, sequences of banana ferritin, an iron storage protein, have been isolated from Cavendish banana. The aim of the research described in this thesis was to evaluate the function of these genes to assess their suitability for the biofortification of banana fruit. In addition, a range of banana-derived promoters were characterised to determine their suitability for controlling the expression of transgenes in banana fruit. Due to the time constraints involved with generating transgenic banana fruit, rice was used as the model crop to investigate the functionality of the banana-derived APsy2a and ferritin genes. Using Agrobacterium-mediated transformation, rice callus was transformed with APsy2a +/- the bacterial-derived carotene desaturase gene (CrtI) each under the control of the constitutive maize poly-ubiquitin promoter (ZmUbi) or seed-specific rice glutelin1 (Gt1) promoter. The maize phytoene synthase (ZmPsy1) gene was included as a control. On selective media, with the exception of ZmUbi-CrtI-transgenic callus, all antibiotic resistant callus displayed a yellow-orange colour from which the presence of â-carotene was demonstrated using Raman spectroscopy. Although the regeneration of plants from yellow-orange callus was difficult, 16 transgenic plants were obtained and characterised from callus transformed with ZmUbi-APys2a alone. At least 50% of the T1 seeds developed a yellow-orange coloured callus which was found to contain levels of â-carotene ranging from 4.6-fold to 72-fold higher than that in non-transgenic rice callus. Using the seed-specific Gt1 promoter, 38 transgenic rice plants were generated from APsy2a-CrtI-transformed callus while 32 plants were regenerated from ZmPsy1-CrtI-transformed callus. However, when analysed for presence of transgene by PCR, all transgenic plants contained the APsy2a, ZmPsy1 or CrtI transgene, with none of the plants found to be co-transformed. Using Raman spectroscopy, no â-carotene was detected in-situ in representative T1 seeds. To investigate the potential of the banana-derived ferritin gene (BanFer1) to enhance iron content, rice callus was transformed with constitutively expressed BanFer1 using the soybean ferritin gene (SoyFer) as a control. A total of 12 and 11 callus lines independently transformed with BanFer1 and SoyFer, respectively, were multiplied and transgene expression was verified by RT-PCR. Pearl’s Prussian blue staining for in-situ detection of ferric iron showed a stronger blue colour in rice callus transformed with BanFer1 compared to SoyFer. Using flame atomic absorption spectrometry, the highest mean amount of iron quantified in callus transformed with BanFer1 was 30-fold while that obtained using the SoyFer was 14-fold higher than the controls. In addition, ~78% of BanFer1-transgenic callus lines and ~27% of SoyFer-transgenic callus lines had significantly higher iron content than the non-transformed controls. Since the genes used for enhancing micronutrient content need to be expressed in banana fruit, the activity of a range of banana-derived, potentially fruit-active promoters in banana was investigated. Using uidA (GUS) as a reporter gene, the function of the Expansin1 (MaExp1), Expansin1 containing the rice actin intron (MaExp1a), Expansin4 (MaExp4), Extensin (MaExt), ACS (MaACS), ACO (MaACO), Metallothionein (MaMT2a) and phytoene synthase (APsy2a) promoters were transiently analysed in intact banana fruit using two transformation methods, particle bombardment and Agrobacterium-mediated infiltration (agro-infiltration). Although a considerable amount of variation in promoter activity was observed both within and between experiments, similar trends were obtained using both transformation methods. The MaExp1 and MaExp1a directed high levels of GUS expression in banana fruit which were comparable to those observed from the ZmUbi and Banana bunchy top virus-derived BT4 promoters that were included as positive controls. Lower levels of promoter activity were obtained in both methods using the MaACO and MaExt promoters while the MaExp4, MaACS, and APsy2a promoters directed the lowest GUS activity in banana fruit. An attempt was subsequently made to use agro-infiltration to assess the expression of pVA biosynthesis genes in banana fruit by infiltrating fruit with constructs in which the ZmUbi promoter controlled the expression of APsy2a +/- CrtI, and with the maize phytoene synthase gene (ZmPsy1) included as a control. Unfortunately, the large amount of variation and inconsistency observed within and between experiments precluded any meaningful conclusions to be drawn. The final component of this research was to assess the level of promoter activity and specificity in non-target tissue. These analyses were done on leaves obtained from glasshouse-grown banana plants stably transformed with MaExp1, MaACO, APsy2a, BT4 and ZmUbi promoters driving the expression of the GUS gene in addition to leaves from a selection of the same transgenic plants which were growing in a field trial in North Queensland. The results from both histochemical and fluorometric GUS assays showed that the MaExp1 and MaACO promoters directed very low GUS activities in leaves of stably transformed banana plants compared to the constitutive ZmUbi and BT4 promoters. In summary, the results from this research provide evidence that the banana phytoene synthase gene (APsy2a) and the banana ferritin gene (BanFer1) are functional, since the constitutive over-expression of each of these transgenes led to increased levels of pVA carotenoids (for APsy2a) and iron content (for BanFer1) in transgenic rice callus. Further work is now required to determine the functionality of these genes in stably-transformed banana fruit. This research also demonstrated that the MaExp1 and MaACO promoters are fruit-active but have low activity in non-target tissue (leaves), characteristics that make them potentially useful for the biofortification of banana fruit. Ultimately, however, analysis of fruit from field-grown transgenic plants will be required to fully evaluate the suitability of pVA biosynthesis genes and the fruit-active promoters for fruit biofortification.

User behaviour modelling in a multi-dimensional environment for personalization and recommendation

Handling information overload online, from the user's point of view is a big challenge, especially when the number of websites is growing rapidly due to growth in e-commerce and other related activities. Personalization based on user needs is the key to solving the problem of information overload. Personalization methods help in identifying relevant information, which may be liked by a user. User profile and object profile are the important elements of a personalization system. When creating user and object profiles, most of the existing methods adopt two-dimensional similarity methods based on vector or matrix models in order to find inter-user and inter-object similarity. Moreover, for recommending similar objects to users, personalization systems use the users-users, items-items and users-items similarity measures. In most cases similarity measures such as Euclidian, Manhattan, cosine and many others based on vector or matrix methods are used to find the similarities. Web logs are high-dimensional datasets, consisting of multiple users, multiple searches with many attributes to each. Two-dimensional data analysis methods may often overlook latent relationships that may exist between users and items. In contrast to other studies, this thesis utilises tensors, the high-dimensional data models, to build user and object profiles and to find the inter-relationships between users-users and users-items. To create an improved personalized Web system, this thesis proposes to build three types of profiles: individual user, group users and object profiles utilising decomposition factors of tensor data models. A hybrid recommendation approach utilising group profiles (forming the basis of a collaborative filtering method) and object profiles (forming the basis of a content-based method) in conjunction with individual user profiles (forming the basis of a model based approach) is proposed for making effective recommendations. A tensor-based clustering method is proposed that utilises the outcomes of popular tensor decomposition techniques such as PARAFAC, Tucker and HOSVD to group similar instances. An individual user profile, showing the user's highest interest, is represented by the top dimension values, extracted from the component matrix obtained after tensor decomposition. A group profile, showing similar users and their highest interest, is built by clustering similar users based on tensor decomposed values. A group profile is represented by the top association rules (containing various unique object combinations) that are derived from the searches made by the users of the cluster. An object profile is created to represent similar objects clustered on the basis of their similarity of features. Depending on the category of a user (known, anonymous or frequent visitor to the website), any of the profiles or their combinations is used for making personalized recommendations. A ranking algorithm is also proposed that utilizes the personalized information to order and rank the recommendations. The proposed methodology is evaluated on data collected from a real life car website. Empirical analysis confirms the effectiveness of recommendations made by the proposed approach over other collaborative filtering and content-based recommendation approaches based on two-dimensional data analysis methods.

Strengthening the role of the adult education sector in training workers for the digital content industries in Australia and Singapore

In 2009, QUT’s Office of Research and the Institute for Adult Learning Singapore funded a six-month pilot project that represented the first stage of a larger international comparative study. The study is the first of its kind to investigate to what extent and how digital content workers’ learning needs are being met by adult education and training in Australia and Singapore. The pilot project involved consolidating key theoretical literature, studies, policies, programs and statistical data relevant to the digital content industries in Australia and Singapore. This had not been done before, and represented new knowledge generation. Digital content workers include professionals within and beyond the creative industries as follows: Visual effects and animation (including virtual reality and 3D products); Interactive multimedia (e.g. websites, CD-ROMs) and software development; Computer and online games; and Digital film & TV production and film & TV post-production. In the last decade, the digital content industries have been recognised as an industry sector of strong and increasing significance. The project compared Australia and Singapore on aspects of the digital content industries’ labour market, skill requirements, human capital challenges, the role of adult education in building a workforce for the digital content industries, and innovation policies. The consolidated report generated from the project formed the basis of the proposal for an ARC Linkage Project application submitted in the May 2010 round.

People, content, location : sweet spotting urban screens for situated engagement

A growing body of research is looking at ways to bring the processes and benefits of online deliberation to the places they are about and in turn allow a larger, targeted proportion of the urban public to have a voice, be heard, and engage in questions of city planning and design. Seeking to take advantage of the civic opportunities of situated engagement through public screens and mobile devices, our research informed a public urban screen content application DIS that we deployed and evaluated in a wide range of real world public and urban environments. For example, it is currently running on the renowned urban screen at Federation Square in Melbourne. We analysed the data from these user studies within a conceptual framework that positions situated engagement across three key parameters: people, content, and location. We propose a way to identify the sweet spot within the nexus of these parameters to help deploy and run interactive systems to maximise the quality of the situated engagement for civic and related deliberation purposes.

Content sharing on public screens: experiences through iterating social and spatial contexts

This paper describes the design and study of public urban screen applications aiming to facilitate urban dwellers to control content shown on public urban screens. Two types of content sharing are presented: aggregating existing social media content about particular locations for sharing, and sharing online videos with collocated people at a public urban screen. The paper describes an exploratory study, an observational study, as well as an interpretational study in regards to application usage and user experience. Sharing content on public urban screens can pique the curiosity of users towards collocated people and the application itself resulting in raised awareness of collocated people.

User participation in the categorisation of the State Library of Queensland digital image collections: characteristics, motivations and experiences

In 2010, the State Library of Queensland (SLQ) donated their out-of-copyright Queensland images to Wikimedia Commons. One direct effect of publishing the collections at Wikimedia Commons is the ability of general audiences to participate and help the library in processing the images in the collection. This paper will discuss a project that explored user participation in the categorisation of the State Library of Queensland digital image collections. The outcomes of this project can be used to gain a better understanding of user participation that lead to improving access to library digital collections. Two techniques for data collection were used: documents analysis and interview. Document analysis was performed on the Wikimedia Commons monthly reports. Meanwhile, interview was used as the main data collection technique in this research. The data collected from document analysis was used to help the researchers to devise appropriate questions for interviews. The interviews were undertaken with participants who were divided into two groups: SLQ staff members and Wikimedians (users who participate in Wikimedia). The two sets of data collected from participants were analysed independently and compared. This method was useful for the researchers to understand the differences between the experiences of categorisation from both the librarians’ and the users’ perspectives. This paper will provide a discussion on the preliminary findings that have emerged from each group participant. This research provides preliminary information about the extent of user participation in the categorisation of SLQ collections in Wikimedia Commons that can be used by SLQ and other interested libraries in describing their digital content by their categorisations to improve user access to the collection in the future.

User-driven quality of experience modelling for mobile video optimisation

The increasing demand for mobile video has attracted much attention from both industry and researchers. To satisfy users and to facilitate the usage of mobile video, providing optimal quality to the users is necessary. As a result, quality of experience (QoE) becomes an important focus in measuring the overall quality perceived by the end-users, from the aspects of both objective system performance and subjective experience. However, due to the complexity of user experience and diversity of resources (such as videos, networks and mobile devices), it is still challenging to develop QoE models for mobile video that can represent how user-perceived value varies with changing conditions. Previous QoE modelling research has two main limitations: aspects influencing QoE are insufficiently considered; and acceptability as the user value is seldom studied. Focusing on the QoE modelling issues, two aims are defined in this thesis: (i) investigating the key influencing factors of mobile video QoE; and (ii) establishing QoE prediction models based on the relationships between user acceptability and the influencing factors, in order to help provide optimal mobile video quality. To achieve the first goal, a comprehensive user study was conducted. It investigated the main impacts on user acceptance: video encoding parameters such as quantization parameter, spatial resolution, frame rate, and encoding bitrate; video content type; mobile device display resolution; and user profiles including gender, preference for video content, and prior viewing experience. Results from both quantitative and qualitative analysis revealed the significance of these factors, as well as how and why they influenced user acceptance of mobile video quality. Based on the results of the user study, statistical techniques were used to generate a set of QoE models that predict the subjective acceptability of mobile video quality by using a group of the measurable influencing factors, including encoding parameters and bitrate, content type, and mobile device display resolution. Applying the proposed QoE models into a mobile video delivery system, optimal decisions can be made for determining proper video coding parameters and for delivering most suitable quality to users. This would lead to consistent user experience on different mobile video content and efficient resource allocation. The findings in this research enhance the understanding of user experience in the field of mobile video, which will benefit mobile video design and research. This thesis presents a way of modelling QoE by emphasising user acceptability of mobile video quality, which provides a strong connection between technical parameters and user-desired quality. Managing QoE based on acceptability promises the potential for adapting to the resource limitations and achieving an optimal QoE in the provision of mobile video content.

CubIT : Large-scale multi-user presentation and collaboration

CubIT is a multi-user, large-scale presentation and collaboration framework installed at the Queensland University of Technology’s (QUT) Cube facility, an interactive facility made up 48 multi-touch screens and very large projected display screens. CubIT was built to make the Cube facility accessible to QUT’s academic and student population. The system allows users to upload, interact with and share media content on the Cube’s very large display surfaces. CubIT implements a unique combination of features including RFID authentication, content management through multiple interfaces, multi-user shared workspace support, drag and drop upload and sharing, dynamic state control between different parts of the system and execution and synchronisation of the system across multiple computing nodes.

Supporting collaboration in large-scale multi-user workspaces

CubIT is a multi-user, large-scale presentation and collaboration framework installed at the Queensland University of Technology’s (QUT) Cube facility, an interactive facility made up 48 multi-touch screens and very large projected display screens. The CubIT system allows users to upload, interact with and share their own content on the Cube’s display surfaces. This paper outlines the collaborative features of CubIT which are implemented via three user interfaces, a large-screen multi-touch interface, a mobile phone and tablet application and a web-based content management system. Each of these applications plays a different role and supports different interaction mechanisms supporting a wide range of collaborative features including multi-user shared workspaces, drag and drop upload and sharing between users, session management and dynamic state control between different parts of the system.

Sleepiness : how a biological drive can influence other risky road user behaviours

The Safe System approach to road safety utilises a holistic view of the interactions among vehicles, roads and road users. Yet, the contribution of each of these factors to crashes is vastly different. The role of road users is widely acknowledged as an overwhelming contributor to road crashes. Substantial gains have been made with improvements to vehicle and roads over a number of years. However, improvements of the road user’s behaviour has been (in some cases) less substantial. A road user behaviour that is relatively unregulated is driver sleepiness, which is part of the ‘fatal five’ of risky road user behaviours. The effect of sleepiness is ubiquitous – sleepiness is a state that most, if not all drivers on our roads has experienced, and is habitually exposed to. The quality and quantity of daily sleep is integral to our level of neurobehavioural performance during wakefulness and as such can have a compounding effect on a number of other risky driving behaviours. This paper will discuss the potential influence of sleepiness as an interceding factor for a number of risky driving behaviours. Little effort has been given to increasing awareness of the deleterious and wide ranging effects that sleepiness has on road safety. Given the wide ranging influence of sleepiness, improvements of ‘sleep health’ as a protective factor at the community or individual level could lead to significant reductions in road trauma and increases of general well being. A discussion of potential actions to reduce sleepiness is required if reductions of road trauma are to continue.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.