XML documents clustering using tensor space model - A preliminary study

A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML. The traditional Vector Space Model (VSM) is not sufficient to represent both the structure and the content of such web documents. Hence in this paper, we introduce a novel method of representing the XML documents in Tensor Space Model (TSM) and then utilize it for clustering. Empirical analysis shows that the proposed method is scalable for a real-life dataset as well as the factorized matrices produced from the proposed method helps to improve the quality of clusters due to the enriched document representation with both the structure and the content information.

A geometrical approach to the motion planning problem for a submerged rigid body

The main focus of this paper is the motion planning problem for a deeply submerged rigid body. The equations of motion are formulated and presented by use of the framework of differential geometry and these equations incorporate external dissipative and restoring forces. We consider a kinematic reduction of the affine connection control system for the rigid body submerged in an ideal fluid, and present an extension of this reduction to the forced affine connection control system for the rigid body submerged in a viscous fluid. The motion planning strategy is based on kinematic motions; the integral curves of rank one kinematic reductions. This method is of particular interest to autonomous underwater vehicles which can not directly control all six degrees of freedom (such as torpedo shaped AUVs) or in case of actuator failure (i.e., under-actuated scenario). A practical example is included to illustrate our technique.

Decoupled trajectory planning for a submerged rigid body subject to dissipative and potential forces

This paper studies the practical but challenging problem of motion planning for a deeply submerged rigid body. Here, we formulate the dynamic equations of motion of a submerged rigid body under the architecture of differential geometric mechanics and include external dissipative and potential forces. The mechanical system is represented as a forced affine-connection control system on the configuration space SE(3). Solutions to the motion planning problem are computed by concatenating and reparameterizing the integral curves of decoupling vector fields. We provide an extension to this inverse kinematic method to compensate for external potential forces caused by buoyancy and gravity. We present a mission scenario and implement the theoretically computed control strategy onto a test-bed autonomous underwater vehicle. This scenario emphasizes the use of this motion planning technique in the under-actuated situation; the vehicle loses direct control on one or more degrees of freedom. We include experimental results to illustrate our technique and validate our method.

Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy.

Flagging Spaces : exploring the myth of the Australian beach as an egalitarian space

The Australian beach is now accepted as a significant part of Australian national culture and identity. However, Huntsman (2001) and Booth (2001) both believe that the beach is dying: “intellectuals have failed to apply to the beach the attention they have lavished on the bush…” (Huntsman 2001, 218). Yet the beach remains a prominent image in contemporary literature and film; authors such as Tim Winton and Robert Drewe frequently set their stories in and around the coast. Although initially considered a space of myth (Fiske, Hodge, and Turner 1987), Meaghan Morris labelled the beach as ‘ordinary’ (1998), and as recently as 2001 in the wake of the Sydney Olympic Games, Bonner, McKee, and Mackay termed the beach ‘tacky’ and ‘familiar’. The beach, it appears, defies an easy categorisation. In fact, I believe the beach is more than merely mythic or ordinary, or a combination of the two. Instead it is an imaginative space, seamlessly shifting its metaphorical meanings dependent on readings of the texts. My studies examine the beach through five common beach myths; this paper will explore the myth of the beach as an egalitarian space. Contemporary Australian national texts no longer conform to these mythical representations – (in fact, was the beach ever a space of equality?), instead creating new definitions for the beach space that continually shifts in meaning. Recent texts such as Tim Winton’s Breath (2008) and Stephen Orr’s Time’s Long Ruin (2010) lay a more complex metaphorical meaning upon the beach space. This paper will explore the beach as a space of egalitarianism in conjunction with recent Australian fiction and films in order to discover how the contemporary beach is represented.

Towards a relational contracting framework in the Australian construction industry : an initial framework

The Australian construction industry is characterized as being a competitive and risky business environment due to lack of cooperation, insufficient trust, ineffective communication and adversarial relationships which are likely lead to poor project performance. Relational contracting (RC) is advocated by literature as an innovative approach to improve the procurement process in the construction industry. Various studies have collectively added to the current knowledge of known RC norms, but there seem to be little effort on investigating the determinants of RC and its impact on project outcomes. In such circumstances, there is lack of evidence and explanation on the manner on how these issues lead to different performance. Simultaneously, the New Engineering Contract (NEC) that embraced the concept of RC is seen as a modern way of contracting and also considered as one of the best approaches to the perennial problem of improving adversarial relationships within the industry. The reality of practice of RC in Australia is investigated through the lens of the NEC. A synthesis of literature views on the concept, processes and tools of RC is first conducted to develop the framework of RC. A case study approach is proposed for an in-depth analysis to explore the critical issues addressed by RC in relation to project performance. Understanding the realities of RC will assist stakeholders in the construction industry with their investment in RC.

A Modified inverse integer Cholesky decorrelation method and the performance on ambiguity resolution

One of the research focuses in the integer least squares problem is the decorrelation technique to reduce the number of integer parameter search candidates and improve the efficiency of the integer parameter search method. It remains as a challenging issue for determining carrier phase ambiguities and plays a critical role in the future of GNSS high precise positioning area. Currently, there are three main decorrelation techniques being employed: the integer Gaussian decorrelation, the Lenstra–Lenstra–Lovász (LLL) algorithm and the inverse integer Cholesky decorrelation (IICD) method. Although the performance of these three state-of-the-art methods have been proved and demonstrated, there is still a potential for further improvements. To measure the performance of decorrelation techniques, the condition number is usually used as the criterion. Additionally, the number of grid points in the search space can be directly utilized as a performance measure as it denotes the size of search space. However, a smaller initial volume of the search ellipsoid does not always represent a smaller number of candidates. This research has proposed a modified inverse integer Cholesky decorrelation (MIICD) method which improves the decorrelation performance over the other three techniques. The decorrelation performance of these methods was evaluated based on the condition number of the decorrelation matrix, the number of search candidates and the initial volume of search space. Additionally, the success rate of decorrelated ambiguities was calculated for all different methods to investigate the performance of ambiguity validation. The performance of different decorrelation methods was tested and compared using both simulation and real data. The simulation experiment scenarios employ the isotropic probabilistic model using a predetermined eigenvalue and without any geometry or weighting system constraints. MIICD method outperformed other three methods with conditioning improvements over LAMBDA method by 78.33% and 81.67% without and with eigenvalue constraint respectively. The real data experiment scenarios involve both the single constellation system case and dual constellations system case. Experimental results demonstrate that by comparing with LAMBDA, MIICD method can significantly improve the efficiency of reducing the condition number by 78.65% and 97.78% in the case of single constellation and dual constellations respectively. It also shows improvements in the number of search candidate points by 98.92% and 100% in single constellation case and dual constellations case.

Relational contracting and its efficacy of project performance in the Australian construction industry

The Australian construction industry is characterized as being a competitive and risky business environment due to lack of cooperation, insufficient trust, ineffective communication and adversarial relationships which are likely lead to poor project performance. Relational contracting (RC) is advocated by literature as an innovative approach to improve the procurement process in the construction industry. Various studies have collectively added to the current knowledge of known RC norms, but there seem to be little effort on investigating the determinants of RC and its efficacy on project outcomes. In such circumstances, there is lack of evidence and explanation on the manner on how these issues lead to different performance. Simultaneously, the New Engineering Contract (NEC) that embraced the concept of RC is seen as a modern way of contracting and also considered as one of the best approaches to the perennial problem of improving adversarial relationships within the industry. The reality of practice of RC in Australia is investigated through the lens of the NEC. A synthesis of literature views on the concept, processes and tools of RC is first conducted to develop the framework of RC. A case study approach is proposed for an in-depth analysis to explore the critical issues addressed by RC in relation to project performance. Understanding the realities of RC will assist stakeholders in the construction industry with their investment in RC.

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Practical application of pseudospectral optimization to robot path planning

To obtain minimum time or minimum energy trajectories for robots it is necessary to employ planning methods which adequately consider the platform’s dynamic properties. A variety of sampling, graph-based or local receding-horizon optimisation methods have previously been proposed. These typically use simplified kino-dynamic models to avoid the significant computational burden of solving this problem in a high dimensional state-space. In this paper we investigate solutions from the class of pseudospectral optimisation methods which have grown in favour amongst the optimal control community in recent years. These methods have high computational efficiency and rapid convergence properties. We present a practical application of such an approach to the robot path planning problem to provide a trajectory considering the robot’s dynamic properties. We extend the existing literature by augmenting the path constraints with sensed obstacles rather than predefined analytical functions to enable real world application.

Trans digital storytelling : everyday activism, mutable identity and the problem of visibility

Mainstream representations of trans people typically run the gamut from victim to mentally ill and are almost always articulated by non-trans voices. The era of user-generated digital content and participatory culture has heralded unprecedented opportunities for trans people who wish to speak their own stories in public spaces. Digital Storytelling, as an easy accessible autobiographic audio-visual form, offers scope to play with multi-dimensional and ambiguous representations of identity that contest mainstream assumptions of what it is to be ‘male’ or ‘female’. Also, unlike mainstream media forms, online and viral distribution of Digital Stories offer potential to reach a wide range of audiences, which is appealing to activist oriented storytellers who wish to confront social prejudices. However, with these newfound possibilities come concerns regarding visibility and privacy, especially for storytellers who are all too aware of the risks of being ‘out’ as trans. This paper explores these issues from the perspective of three trans storytellers, with reference to the Digital Stories they have created and shared online and on DVD. These examplars are contextualised with some popular and scholarly perspectives on trans representation, in particular embodied and performed identity. It is contended that trans Digital Stories, while appearing in some ways to be quite conventional, actually challenge common notions of gender identity in ways that are both radical and transformative.

The impact of online reviews on hotel booking intentions and trust

A growing reliance on the Internet as an information source when making choices about tourism products raises the need for more research into electronic word of mouth. Within a hotel context, this study explores the role of four key factors that influence perceptions of trust and consumer choice. An experimental design is used to investigate four independent variables: the target of the review (core or interpersonal); overall valence of a set of reviews (positive or negative); framing of reviews (what comes first: negative or positive information); and whether or not a consumer generated numerical rating is provided together with the written text. Consumers seem to be more influenced by early negative information, especially when the overall set of reviews is negative. However, positively framed information together with numerical rating details increases both booking intentions and consumer trust. The results suggest that consumers tend to rely on easy-to-process information, when evaluating a hotel based upon reviews. Higher levels of trust are also evident when a positively framed set of reviews focused on interpersonal service.

A survey on the relationship between trust and interest similarity in online social networks

A remarkable growth in quantity and popularity of online social networks has been observed in recent years. There is a good number of online social networks exists which have over 100 million registered users. Many of these popular social networks offer automated recommendations to their users. This automated recommendations are normally generated using collaborative filtering systems based on the past ratings or opinions of the similar users. Alternatively, trust among the users in the network also can be used to find the neighbors while making recommendations. To obtain the optimum result, there must be a positive correlation exists between trust and interest similarity. Though the positive relations between trust and interest similarity are assumed and adopted by many researchers; no survey work on real life people’s opinion to support this hypothesis is found. In this paper, we have reviewed the state-of-the-art research work on trust in online social networks and have presented the result of the survey on the relationship between trust and interest similarity. Our result supports the assumed hypothesis of positive relationship between the trust and interest similarity of the users.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.