Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

Towards modelling web search behaviour : integrating users’ cognitive styles

With the rapid growth of information on the Web, the study of information searching has let to an increased interest. Information behaviour (IB) researchers and information systems (IS) developers are continuously exploring user - Web search interactions to understand and to help users to provide assistance with their information searching. In attempting to develop models of IB, several studies have identified various factors that govern user's information searching and information retrieval (IR), such as age, gender, prior knowledge and task complexity. However, how users' contextual factors, such as cognitive styles, affect Web search interactions has not been clearly explained by the current models of Web Searching and IR. This study explores the influence of users' cognitive styles on their Web search behaviour. The main goal of the study is to enhance Web search models with a better understanding of how these cognitive styles affect Web searching. Modelling Web search behaviour with a greater understanding of user's cognitive styles can help information science researchers and IS designers to bridge the semantic gap between the user and the IS. To achieve the aims of the study, a user study with 50 participants was conducted. The study adopted a mixed method approach incorporating several data collection strategies to gather a range of qualitative and quantitative data. The study utilised pre-search and post-search questionnaires to collect the participants' demographic information and their level of satisfaction about the search interactions. Riding's (1991) Cognitive Style Analysis (CSA) test was used to assess the participants' cognitive styles. Participants completed three predesigned search tasks and the whole user - web search interactions, including thinkaloud, were captured using a monitoring program. Data analysis involved several qualitative and quantitative techniques: the quantitative data gave raise to detailed findings about users' Web searching and cognitive styles, the qualitative data enriched the findings with illustrative examples. The study results provide valuable insights into Web searching behaviour among different cognitive style users. The findings of the study extend our understanding of Web search behaviour and how users search information on the Web. Three key study findings emerged: • Users' Web search behaviour was demonstrated through information searching strategies, Web navigation styles, query reformulation behaviour and information processing approaches while performing Web searches. The manner in which these Web search patterns were demonstrated varied among the users with different cognitive style groups. • Users' cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. Users with particular cognitive styles followed certain Web search patterns. • Fundamental relationships were evident between users' cognitive styles and their Web search behaviours; and these relationships can be illustrated through modelling Web search behaviour. Two models that depict the associations between Web search interactions, user characteristics and users' cognitive styles were developed. These models provide a greater understanding of Web search behaviour from the user perspective, particularly how users' cognitive styles influence their Web search behaviour. The significance of this research is twofold: it will provide insights for information science researchers, information system designers, academics, educators, trainers and librarians who want to better understand how users with different cognitive styles perform information searching on the Web; at the same time, it will provide assistance and support to the users. The major outcomes of this study are 1) a comprehensive analysis of how users search the Web; 2) extensive discussion on the implications of the models developed in this study for future work; and 3) a theoretical framework to bridge high-level search models and cognitive models.

Exploiting Web 2.0 technologies to forge live connectedness in class

The economics of supporting learning has seen institutional encouragement of a wide range of blended learning initiatives in face to face and online teaching and learning. This has become one of the key drivers for the adoption of technology in teaching, in a manner occassionally guilty of putting the cart before the horse. Learning spaces are increasingly equipped with a dizzying array of technological options testifying to institutional and governmental investment and commitment in supporting face to face blended learning (QUT, 2011, C/4.2). Yet innovation within traditional learning and teaching models faces a number of challenges both at an institutional level and at the teaching coal face. Web 2.0 technologies present a vast array of opportunities to harness and capture the attention of students in engaging learning opportunitites. This presentation will explore technologies supportive of active learning pedagogies.

A social matching system : using implicit and explicit information for personalized recommendation in online dating service

Online dating websites enable a specific form of social networking and their efficiency can be increased by supporting proactive recommendations based on participants' preferences with the use of data mining. This research develops two-way recommendation methods for people-to-people recommendation for large online social networks such as online dating networks. This research discovers the characteristics of the online dating networks and utilises these characteristics in developing efficient people-to-people recommendation methods. Methods developed support improved recommendation accuracy, can handle data sparsity that often comes with large data sets and are scalable for handling online networks with a large number of users.

Not losing the plot : creating, collecting and curating qualitative data through a web-based application

Collecting regular personal reflections from first year teachers in rural and remote schools is challenging as they are busily absorbed in their practice, and separated from each other and the researchers by thousands of kilometres. In response, an innovative web-based solution was designed to both collect data and be a responsive support system for early career teachers as they came to terms with their new professional identities within rural and remote school settings. Using an emailed link to a web-based application named goingok.com, the participants are charting their first year plotlines using a sliding scale from ‘distressed’, ‘ok’ to ‘soaring’ and describing their self-assessment in short descriptive posts. These reflections are visible to the participants as a developing online journal, while the collections of de-identified developing plotlines are visible to the research team, alongside numerical data. This paper explores important aspects of the design process, together with the challenges and opportunities encountered in its implementation. A number of the key considerations for choosing to develop a web application for data collection are initially identified, and the resultant application features and scope are then examined. Examples are then provided about how a responsive software development approach can be part of a supportive feedback loop for participants while being an effective data collection process. Opportunities for further development are also suggested with projected implications for future research.

Finite element analysis of hollow flange beams with web stiffeners

A new cold-formed and resistance welded section known as the Hollow Flange Beam (HFB) has been developed recently in Australia. In contrast to the common lateral torsional buckling mode of I-beams, this unique section comprising two stiff triangular flanges and a slender web is susceptible to a lateral distortional buckling mode of failure involving lateral deflection, twist, and cross-section change due to web distortion. This lateral distortional buckling behavior has been shown to cause significant reduction of the available flexural capacity of HFBs. An investigation using finite element analyses and large scale experiments was carried out into the use of transverse web plate stiffeners to improve the lateral buckling capacity of HFBs. This paper presents the details of the finite element model and analytical results. The experimental procedure and results are outlined in a companion paper at this conference.

Buckling experiments on hollow flange beams with web stiffeners

A new cold-formed and resistance welded section known as the Hollow Flange Beam (HFB) has been developed recently in Australia. In contrast to the common lateral torsional buckling mode of I-beams, this unique section comprising two stiff triangular flanges and a slender web is susceptible to a lateral distortional buckling mode of failure involving lateral deflection, twist and cross-section change due to web distortion. This lateral distortional buckling behaviour has been shown to cause significant reduction of the available flexural strength of HFBs. An investigation using finite element analyses and large scale experiments was carried out into the use of transverse web plate stiffeners to improve the lateral buckling capacity of HFBs. This paper presents the details of the experimental investigation, the results, and the final stiffener arrangement whereas the details of the finite element analyses are presented in a companion paper at this conference.

Finite-element analysis of hollow flange beams with web stiffeners

A new cold-formed and resistance-welded section known as the hollow flange beam (HFB) has been developed recently in Australia. In contrast to the common lateral-torsional buckling mode of I-beams, this unique section comprising two stiff triangular flanges and a slender web is susceptible to a lateral-distortional buckling mode of failure involving lateral deflection, twist, and cross-section change due to web distortion. This lateral-distortional buckling behavior has been shown to cause significant reduction of the available flexural capacity of HFBs. An investigation using finite-element analyses and large-scale experiments was carried out into the use of transverse web plate stiffeners to improve the lateral buckling capacity of HFBs. This paper presents the details of the finite-element model and analytical results. The experimental procedure and results are outlined in a companion paper.

Buckling experiments on hollow flange beams with web stiffeners

The hollow flange beam (HFB) is a new cold-formed and resistance-welded section developed in Australia. Due to its unique geometry comprising two stiff triangular flanges and a slender web, the HFB is susceptible to a lateral-distortional buckling mode of failure involving web distortion. Investigation using finite-element analyses showed that the use of transverse web plate stiffeners effectively eliminated lateral-distortional buckling of HFBs and thus any associated reduction in flexural capacity. A detailed experimental investigation was then carried out to validate the results from the finite-element analysis and to improve the stiffener configuration further. This led to the development of a special stiffener that is screw-fastened to the flanges on alternate sides of the web. This paper presents the details of the experimental investigations, the results, and the final stiffener arrangement whereas the details of the finite-element analyses are presented in a companion paper.

Shear capacity of lipped channel beams with web openings : design rules and improvements

Cold-formed steel Lipped Channel Beams (LCB) with web openings are commonly used as floor joists and bearers in building structures. Shear behaviour of these beams is more complicated and their shear capacities are considerably reduced by the presence of web openings. Hence detailed numerical and experimental studies of simply supported LCBs under a mid-span load with aspect ratios of 1.0 and 1.5 were undertaken to investigate the shear behaviour and strength of LCBs with web openings. Experimental and numerical results showed that the current design rules in cold-formed steel structures design codes are very conservative. Improved design equations were therefore proposed for the shear strength of LCBs with web openings based on both experimental and numerical results. This research showed a significant reduction in shear capacities of LCBs when large web openings are included for the purpose of locating building services. A cost effective method of eliminating such detrimental effects of large circular web openings was also therefore investigated using experimental and numerical studies. For this purpose LCBS were reinforced using plate, stud, transverse and sleeve stiffeners with varying sizes and thicknesses that were welded and screw-fastened to the web of LCBs. These studies showed that plate stiffeners were the most suitable. Suitable screw-fastened plate stiffener arrangements with optimum thicknesses were then proposed for LCBs with web openings to restore their original shear capacities. This paper presents the details of finite element analyses and experiments of LCBs with web openings in shear, and the development of improved shear design rules. It then describes the experimental and numerical studies to determine the optimum plate stiffener arrangements and the results. The proposed shear design rules in this paper can be considered for inclusion in the future versions of cold-formed steel design codes.

Practical guidance for the use of a pattern-matching technique in case-study research : a case presentation

This paper reports on a study that demonstrates how to apply pattern matching as an analytical method in case-study research. Case-study design is appropriate for the investigation of highly-contextualized phenomena that occur within the social world. Case-study design is considered a pragmatic approach that permits employment of multiple methods and data sources in order to attain a rich understanding of the phenomenon under investigation. The findings from such multiple methods can be reconciled in case-study analysis, specifically through a pattern-matching technique. Although this technique is theoretically explained in the literature, there is scant guidance on how to apply the method practically when analyzing data. This paper demonstrates the steps taken during pattern matching in a completed case-study project that investigated the influence of cultural diversity in a multicultural nursing workforce on the quality and safety of patient care. The example highlighted in this paper contributes to the practical understanding of the pattern-matching process, and can also make a substantial contribution to case-study methods.

Modeling users’ web search behavior and their cognitive styles

Previous studies have shown that users’ cognitive styles play an important role during Web searching. However, only limited studies have showed the relationship between cognitive styles and Web search behavior. Most importantly, it is not clear which components of Web search behavior are influenced by cognitive styles. This paper examines the relationships between users’ cognitive styles and their Web searching and develops a model that portrays the relationship. The study uses qualitative and quantitative analyses to inform the study results based on data gathered from 50 participants. A questionnaire was utilised to collect participants’ demographic information, and Riding’s (1991) Cognitive Style Analysis (CSA) test to assess their cognitive styles. Results show that users’ cognitive styles influenced their information searching strategies, query reformulation behaviour, Web navigational styles and information processing approaches. The user model developed in this study depicts the fundamental relationships between users’ Web search behavior and their cognitive styles. Modeling Web search behavior with a greater understanding of user’s cognitive styles can help information science researchers and information systems designers to bridge the semantic gap between the user and the systems. Implications of the research for theory and practice, and future work are discussed.

The apps industry

Australian apps developers typify global industry segmentation, varying in function, focus, employment situation and background. They range from freelancers contracted to build apps on demand and venture capital-backed or bootstrapped startups, to specialist app studios and full service digital agencies for whom apps are one among many services that may include web development, marketing, advertising, business strategy, branding and games development.

The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.