User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

Connecting users and items with weighted tags for personalized item recommendations

Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

A hybrid recommender systems based on weighted tags

Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.

Remixing social media for location sharing on public urban screens

This paper introduces Sapporo World Window (hereafter SWW), an interactive social media mash-up deployed in a newly built urban public underground space utilising ten public displays and urban dwellers’ mobile phones. SWW enables users to share their favourite locations with fellow citizens and visitors through integrating various social media contents to a coherent whole. The system aims to engage citizens in socio-cultural and technological interactions, turning the underground space into a creative and lively social space. We present first insight from an initial user study in a real world setting.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

Students' perceptions of the relevance of mathematics in engineering

In this paper, we report on the findings of an exploratory study into the experience of students as they learn first year engineering mathematics. Here we define engineering as the application of mathematics and sciences to the building and design of projects for the use of society (Kirschenman and Brenner 2010)d. Qualitative and quantitative data on students' views of the relevance of their mathematics study to their engineering studies and future careers in engineering was collected. The students described using a range of mathematics techniques (mathematics skills developed, mathematics concepts applied to engineering and skills developed relevant for engineering) for various usages (as a subject of study, a tool for other subjects or a tool for real world problems). We found a number of themes relating to the design of mathematics engineering curriculum emerged from the data. These included the relevance of mathematics within different engineering majors, the relevance of mathematics to future studies, the relevance of learning mathematical rigour, and the effectiveness of problem solving tasks in conveying the relevance of mathematics more effectively than other forms of assessment. We make recommendations for the design of engineering mathematics curriculum based on our findings.

Lego robotics : an authentic problem solving tool?

With the current curriculum focus on correlating classroom problem solving lessons to real-world contexts, are LEGO robotics an effective problem solving tool? This present study was designed to investigate this question and to ascertain what problem solving strategies primary students engaged with when working with LEGO robotics and whether the students were able to effectively relate their problem solving strategies to real-world contexts. The qualitative study involved 23 Grade 6 students participating in robotics activities. The study included data collected from researcher observations of student problem solving discussions, collected software programs, and data from a student completed questionnaire. Results from the study indicated that the robotic activities assisted students to reflect on the problem-solving decisions they made. The study also highlighted that the students were able to relate their problem solving strategies to real-world contexts. The study demonstrated that while LEGO robotics can be considered useful problem solving tools in the classroom, careful teacher scaffolding needs to be implemented in regards to correlating LEGO with authentic problem solving. Further research in regards to how teachers can best embed real-world contexts into effective robotics lessons is recommended.

Collaborative destination branding : planning for tourism development through design in the Waterfall Way, NSW, Australia

This thesis develops, applies and analyses a collaborative design methodology for branding a tourism destination. The area between the Northern Tablelands and the Mid-North Coast of New South Wales, Australia, was used as a case study for this research. The study applies theoretical concepts of systems thinking and complexity to the real world, and tests the use of design as a social tool to engage multiple stakeholders in planning. In this research I acknowledge that places (and destinations) are socially constructed through people's interactions with their physical and social environments. This study explores a methodology that is explicit about the uncertainties of the destination’s system, and that helps to elicit knowledge and system trends. The collective design process used the creation of brand concepts, elements and strategies as instruments to directly engage stakeholders in the process of reflecting about their places and the issues related to tourism activity in the region. The methods applied included individual conversations and collaborative design sessions to elicit knowledge from local stakeholders. Concept maps were used to register and interpret information released throughout the process. An important aspect of the methodology was to bring together different stakeholder groups and translate the information into a common language that was understandable by all participants. This work helped release significant information as to what kind of tourism activity local stakeholders are prepared to receive and support. It also helped the emergence of a more unified regional identity. The outcomes delivered by the project (brand, communication material and strategies) were of high quality and in line with the desires and expectation of the local hosts. The process also reinforced local sense of pride, belonging and conservation. Furthermore, interaction between participants from different parts of the region triggered some self organising activity around the brand they created together. A major contribution of the present work is the articulation of an inclusive methodology to facilitate the involvement of locals into the decision-making process related to tourism planning. Of particular significance is the focus on the social construction of meaning in and through design, showing that design exercises can have significant social impact – not only on the final product, but also on the realities of the people involved in the creative process.

Building support for learning within a Doctor of Education programme

Professional doctorates were introduced in the 1990s for practitioners to research ‘real-world’ problems relevant to their respective workplace communities and contexts. An array of difficulties faces professional doctoral students as they transition from professionals to practitioner researchers. This study sought to understand the learning journey of a cohort of students at an Australian university and to assess whether the cohort approach provided the necessary support for students to reach their scholarly destinations. Throughout the first 18 months of the programme, focus group interviews and surveys were conducted to gauge students’ experiences and to evaluate developments for support within the programme. Utilising a socio-cultural perspective helped identify and explain the importance of shared practice in fostering learning, the development of academic and researcher identities, and the role of communities of practice. Challenges of managing time and overcoming the professional and academe divide were facilitated by the evolving developments of the programme.

Ezine and iRadio as knowledge creation metaphors for scaffolding learning in physical and virtual learning spaces

eZine and iRadio represent metaphors for multimedia communication on the Internet. Participating students experience a simulated Internet publishing environment in both their classroom and virtual learning environment. This chapter presents an autoethnographic account highlighting the voices of the learning designer and the teacher and provides evidence of the planning and implementation of two tertiary music elective courses over three iterations of each course. A blended learning environment was incorporated within each elective music course and a collaborative approach to development between lecturers, tutors, learning and technological designers using an iterative research design. The research suggests that learning design which provides real world examples and resources integrating authentic task design into their unit can provide meaningful and engaging experiences for students. The dialogue between learning designers and teachers and iterative review of the learning process and student outcomes, we believe, has engaged students meaningfully to achieve transferable learning outcomes.

Evaluating medical information retrieval

This paper presents a framework for evaluating information retrieval of medical records. We use the BLULab corpus, a large collection of real-world de-identified medical records. The collection has been hand coded by clinical terminol- ogists using the ICD-9 medical classification system. The ICD codes are used to devise queries and relevance judge- ments for this collection. Results of initial test runs using a baseline IR system are provided. Queries and relevance judgements are online to aid further research in medical IR. Please visit: http://koopman.id.au/med_eval.

Bouncing back : the role of design in facilitating students to understand and deal with adversity

After state-wide flooding and a category-5 tropical cyclone, three-quarters of the state of Queensland was declared a disaster zone in early 2011. This deluge of adversity had a significant impact on university students, a few weeks prior to the start of the academic semester. The purpose of this paper is to examine the role that design plays in facilitating students to understand and respond to, adversity. The participants of this study were second and fourth year architectural design students at a large Australian University, in Queensland. As a part of their core architectural design studies, students were required to provide architectural responses to the recent catastrophic events in Queensland. Qualitative data was obtained through student surveys, work design work submitted by students and a survey of guests who attending an exhibition of the student work. The results of this research showed that the students produced more than just the required set of architectural drawings, process journals and models, but also recognition of the important role that the affective dimension of the flooding event and the design process played in helping them to both understand and respond to, adversity. They held the ‘real world’ experience and practical aspect of the assessment in higher regard than their typical focus on aesthetics and the making of iconic design. Perhaps most importantly, the students recognised that this process allowed them to have a voice, and a means to respond to adversity through the powerful language of design.

Complementary use of modeling grammars

Conceptual modeling continues to be an important means for graphically capturing the requirements of an information system. Observations of modeling practice suggest that modelers often use multiple modeling grammars in combination to articulate various aspects of real-world domains. We extend an ontological theory of representation to suggest why and how users employ multiple conceptual modeling grammars in combination. We provide an empirical test of the extended theory using survey data and structured interviews about the use of traditional and structured analysis grammars within an automated tool environment. We find that users of the analyzed tool combine grammars to overcome the ontological incompleteness that exists in each grammar. Users further selected their starting grammar from a predicted subset of grammars only. The qualitative data provides insights as to why some of the predicted deficiencies manifest in practice differently than predicted.