Generating product feature hierarchy from product reviews

User generated information such as product reviews have been booming due to the advent of web 2.0. In particular, rich information associated with reviewed products has been buried in such big data. In order to facilitate identifying useful information from product (e.g., cameras) reviews, opinion mining has been proposed and widely used in recent years. In detail, as the most critical step of opinion mining, feature extraction aims to extract significant product features from review texts. However, most existing approaches only find individual features rather than identifying the hierarchical relationships between the product features. In this paper, we propose an approach which finds both features and feature relationships, structured as a feature hierarchy which is referred to as feature taxonomy in the remainder of the paper. Specifically, by making use of frequent patterns and association rules, we construct the feature taxonomy to profile the product at multiple levels instead of single level, which provides more detailed information about the product. The experiment which has been conducted based upon some real world review datasets shows that our proposed method is capable of identifying product features and relations effectively.

Social NUI: Social perspectives in natural user interfaces

Natural User Interfaces (NUI) offer rich ways for interacting with the digital world that make innovative use of existing human capabilities. They include and often combine different input modalities such as voice, gesture, eye gaze, body interactions, touch and touchless interactions. However much of the focus of NUI research and development has been on enhancing the experience of individuals interacting with technology. Effective NUIs must also acknowledge our innately social characteristics, and support how we communicate with each other, play together, learn together and collaboratively work together. This workshop concerns the social aspects of NUI. The workshop seeks to better understand the social uses and applications of these new NUI technologies -- how we design these technologies for new social practices and how we understand the use of these technologies in key social contexts.

Measuring the impact of burn scarring on health-related quality of life: Development and preliminary content validation of the Brisbane Burn Scar Impact Profile (BBSIP) for children and adults

INTRODUCTION No burn-scar specific, health-related quality of life (HRQOL) measure exists. This study aimed to develop a patient-reported, evaluative HRQOL measure to assess the impact of burn scarring in children and adults. METHOD Semi-structured interviews, content validation surveys, and cognitive interviews were used to develop and test content validity of a new measure - the Brisbane Burn Scar Impact Profile (BBSIP). RESULTS Participants comprised Australian adults (n=23) and children (n=19) with burn scarring; caregivers of children with burn scarring (n=28); and international scar management experts (n=14). Items distinct from other burn scar measures emerged. Four versions of the BBSIP were developed; one for children aged 8-18 years, one for adults, one for caregivers (as proxies for children aged less than 8-years), and one for caregivers of children aged 8-18 years. Preliminary content validity of the BBSIP was supported. Final items covered physical and sensory symptoms; emotional reactions; impact on social functioning and daily activities; impact of treatment; and environmental factors. CONCLUSION The BBSIP was developed to assess burn-scar specific HRQOL and will be available at http://www.coolburns.com.au under a creative commons license. Further testing is underway.

User centred design for engineering e-government web usability

E-government provides a platform for governments to implement web enabled services that facilitate communication between citizens and the government. However, technology driven design approach and limited understanding of citizens' requirements, have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of User Centred Design and examining them based on the empirical data derived from case study of the Scottish Executive website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice.

Making usability affordable in the design of e-government services: User-centred design for public sector websites

E-government provides a platform for governments to implement web-enabled services that facilitate communication between citizens and the government. However, technology-driven design approach and limited understanding of citizens' requirements have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User-Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of UCD and examining them based on the empirical data derived from case study of the Scottish Executive (SE) website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations, which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice. © Copyright 2010 Inderscience Enterprises Ltd.

Dressing up Tinderella: Interrogating authenticity claims on the mobile dating app Tinder

Mobile dating applications (‘apps’) have increased in popularity over recent years, with Tinder among the first to break into the mainstream heterosexual market. Since mobile dating intensifies the need to confirm that potential dates are not misrepresenting themselves and are safe to meet in person, Tinder’s success indicates that it has allayed these concerns regarding the authenticity of its users. This article combines Giddens’ conceptualization of authenticity, as the ability to reference a coherent biographical narrative, with Callon’s sociology of translation to investigate Tinder’s framing of authenticity within mobile dating. Applying a walkthrough method that interrogates Tinder’s technological architecture, promotional materials, and related media, this hybrid theoretical framework is used to identify how Tinder configures an actor-network that establishes its app as the solution to users’ concerns, enrols individuals in using its features in authenticity claims, and popularizes Tinder’s framing across public discourse. This network of human and non-human actors frames authenticity as being established through one’s Facebook profile and adherence to normative standards relating to age, gender, ethnicity, and socioeconomic status. However, user discourses on other social media identify and challenge negative outcomes of this framing, with normativity fostering discrimination and Facebook verification failing to prevent abusive behavior. This case study of Tinder paves the way for future investigation into user responses to its framing. Further, it demonstrates the efficacy and broader applicability of this theoretical approach for identifying both human and technological influences on the construction of authenticity with digital media.

Journalistic branding on Twitter: A representative study of Australian journalists’ profile descriptions

While journalism scholarship on Twitter has expanded significantly in recent years, journalists’ use of the social networking platform for self-promotion and branding has only recently received attention. Yet, as Twitter is becoming important for journalists to build economic and social capital, journalistic branding is increasingly relevant to study. This article reports the results from a study of 4189 Australian journalists’ Twitter accounts to examine their approaches to self-presentation and branding in their profile information. We find that journalists self-identify primarily through professional characteristics, but a significant number also mix this with personal information. Yet, they are also wary of providing personal information, with one-third including a disclaimer that their views are their own. Whereas only small differences could be found along gender lines, more significant differences existed in terms of whether journalists worked in metropolitan or regional areas and the nature of their employers’ main platform of distribution.

Evaluation of a 7-gene genetic profile for athletic endurance phenotype in Ironman championship triathletes

Polygenic profiling has been proposed for elite endurance performance, using an additive model determining the proportion of optimal alleles in endurance athletes. To investigate this model’s utility for elite triathletes, we genotyped seven polymorphisms previously associated with an endurance polygenic profile (ACE Ins/Del, ACTN3 Arg577Ter, AMPD1 Gln12Ter, CKMM 1170bp/985+185bp, HFE His63Asp, GDF8 Lys153Arg and PPARGC1A Gly482Ser) in a cohort of 196 elite athletes who participated in the 2008 Kona Ironman championship triathlon. Mean performance time (PT) was not significantly different in individual marker analysis. Age, sex, and continent of origin had a significant influence on PT and were adjusted for. Only the AMPD1 endurance-optimal Gln allele was found to be significantly associated with an improvement in PT (model p=5.79 x 10-17, AMPD1 genotype p=0.01). Individual genotypes were combined into a total genotype score (TGS); TGS distribution ranged from 28.6 to 92.9, concordant with prior studies in endurance athletes (mean±SD: 60.75±12.95). TGS distribution was shifted toward higher TGS in the top 10% of athletes, though the mean TGS was not significantly different (p=0.164) and not significantly associated with PT even when adjusted for age, sex, and origin. Receiver operating characteristic curve analysis determined that TGS alone could not significantly predict athlete finishing time with discriminating sensitivity and specificity for three outcomes (less than median PT, less than mean PT, or in the top 10%), though models with the age, sex, continent of origin, and either TGS or AMPD1 genotype could. These results suggest three things: that more sophisticated genetic models may be necessary to accurately predict athlete finishing time in endurance events; that non-genetic factors such as training are hugely influential and should be included in genetic analyses to prevent confounding; and that large collaborations may be necessary to obtain sufficient sample sizes for powerful and complex analyses of endurance performance.

Clinical relevance of MTHFR, eNOS, ACE, and ApoE gene polymorphisms and serum vitamin profile among Malay patients with ischemic stroke

Background The purpose of this study was threefold. First, it was to determine the relationship between serum vitamin profiles and ischemic stroke. The second purpose was to investigate the association of methylenetetrahydrofolate reductase (MTHFR), endothelial nitric oxide synthase (eNOS), angiotensin converting enzyme (ACE), and apolipoprotein-E (ApoE) gene polymorphisms with ischemic stroke and further correlate with serum vitamin profiles among ischemic stroke patients. The third purpose of the study was to highlight the interaction of MTHFR and eNOS haplotypes with serum vitamin profiles and ischemic stroke risks. Methods Polymorphisms of these genes were analyzed in age-, sex-, and ethnicity-matched case–controls (n = 594); serum vitamin profiles were determined using immunoassays. Results The MTHFR 677C>T, 1298A>C, eNOS intron 4a/b, and ApoE polymorphisms were significantly associated with the increased risk of ischemic stroke. Elevated serum homocysteine and vitamin B12 levels were associated with MTHFR 677C>T and eNOS intron 4a/b polymorphisms. The ApoE and eNOS −786T>C polymorphisms were associated with increased serum vitamin B12 levels. However, none of the polymorphisms influenced serum folate levels except for the MTHFR 1298A>C. Different patterns of MTHFR and eNOS haplotypes tend to affect serum vitamin profiles to different degrees, which contribute to either different susceptibility risk or protective effect on ischemic stroke. Overall, increased levels of serum homocysteine and vitamin B12 levels were associated with higher risk of ischemic stroke in the investigated population. Conclusions The present study suggests that the genotypes and haplotypes of MTHFR 677C>T and eNOS intron 4a/b polymorphisms are potential serum biomarkers in the pathophysiological processes of ischemic stroke, by modulating homocysteine and vitamin B12 levels.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Elucidating the neuropsychological profile of apathetic syndrome and disinhibition syndrome in a brain-injured population in Oman

The purpose of this study was to compare the neuropsychological performance of two frontal dysexecutive phenotypes - disinhibited&' syndrome (DS) and &'apathetic&' syndrome (AS) following a traumatic brain injury in a non-western population, Oman. Methods: The study compared the performance of DS and AS in neuropsychological measures including those tapping into verbal reasoning ability/working memory/attention planning/goal-directed behavior and affective ranges. Results: The present analysis showed that DS and AS participants did not differ on indices measuring working memory/attention and affective ranges. However, the two cohorts differed significantly in measures of planning/goal-directed behaviour. Conclusion: This study lays the groundwork for further scrutiny in delineating the different characteristics of what has been previously labelled as frontal dysexecutive phenotype. This study indicates that DS and AS are marked with specific neuropsychological deficits.

The profile of psychiatric symptoms exacerbated by methamphetamine use

Background Methamphetamine use can produce symptoms almost indistinguishable from schizophrenia. Distinguishing between the two conditions has been hampered by the lack of a validated symptom profile for methamphetamine-induced psychiatric symptoms. We use data from a longitudinal cohort study to examine the profile of psychiatric symptoms that are acutely exacerbated by methamphetamine use. Methods 164 methamphetamine users, who did not meet DSM-IV criteria for a lifetime primary psychotic disorder, were followed monthly for one year to assess the relationship between days of methamphetamine use and symptom severity on the 24-item Brief Psychiatric Rating Scale. Exacerbation of psychiatric symptoms with methamphetamine use was quantified using random coefficient models. The dimensions of symptom exacerbation were examined using principal axis factoring and a latent profile analysis. Results Symptoms exacerbated by methamphetamine loaded on three factors: positive psychotic symptoms (suspiciousness, unusual thought content, hallucinations, bizarre behavior); affective symptoms (depression, suicidality, guilt, hostility, somatic concern, self-neglect); and psychomotor symptoms (tension, excitement, distractibility, motor hyperactivity). Methamphetamine use did not significantly increase negative symptoms. Vulnerability to positive psychotic and affective symptom exacerbation was shared by 28% of participants, and this vulnerability aligned with a past year DSM-IV diagnosis of substance-induced psychosis (38% vs. 22%, _2 (df1) = 3.66, p = 0.056). Conclusion Methamphetamine use produced a symptom profile comprised of positive psychotic and affective symptoms, which aligned with a diagnosis of substance-induced psychosis, with no evidence of a negative syndrome.

Investigation of a suicide ideation risk profile in people with co-occurring depression and substance use disorder

Disengagement from services is common before suicide, hence identifying factors at treatment presentation that predict future suicidality is important. This article explores risk profiles for suicidal ideation among treatment seekers with depression and substance misuse. Participants completed assessments at baseline and 6 months. Baseline demographics, psychiatric history, and current symptoms were entered into a decision tree to predict suicidal ideation at follow-up. Sixty-three percent of participants at baseline and 43.5% at follow-up reported suicidal ideation. Baseline ideation most salient when psychiatric illness began before adulthood, increasing the rate of follow-up ideation by 16%. Among those without baseline ideation, dysfunctional attitudes were the most important risk factor, increasing rates of suicidal ideation by 35%. These findings provide evidence of factors beyond initial diagnoses that increase the likelihood of suicidal ideation and are worthy of clinical attention. In particular, providing suicide prevention resources to those with high dysfunctional attitudes may be beneficial.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.