Integrating collaborative filtering and matching-based search for product recommendation

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and thus help them in making good decisions about which product to buy from the vast number of product choices available to them. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based recommender system approaches. These approaches are not suitable for recommending luxurious and infrequently purchased products as they rely on a large amount of ratings data that is not usually available for such products. This research aims to explore novel approaches for recommending infrequently purchased products by exploiting user generated content such as user reviews and product click streams data. From reviews on products given by the previous users, association rules between product attributes are extracted using an association rule mining technique. Furthermore, from product click streams data, user profiles are generated using the proposed user profiling approach. Two recommendation approaches are proposed based on the knowledge extracted from these resources. The first approach is developed by formulating a new query from the initial query given by the target user, by expanding the query with the suitable association rules. In the second approach, a collaborative-filtering recommender system and search-based approaches are integrated within a hybrid system. In this hybrid system, user profiles are used to find the target user’s neighbour and the subsequent products viewed by them are then used to search for other relevant products. Experiments have been conducted on a real world dataset collected from one of the online car sale companies in Australia to evaluate the effectiveness of the proposed recommendation approaches. The experiment results show that user profiles generated from user click stream data and association rules generated from user reviews can improve recommendation accuracy. In addition, the experiment results also prove that the proposed query expansion and the hybrid collaborative filtering and search-based approaches perform better than the baseline approaches. Integrating the collaborative-filtering and search-based approaches has been challenging as this strategy has not been widely explored so far especially for recommending infrequently purchased products. Therefore, this research will provide a theoretical contribution to the recommender system field as a new technique of combining collaborative-filtering and search-based approaches will be developed. This research also contributes to a development of a new query expansion technique for infrequently purchased products recommendation. This research will also provide a practical contribution to the development of a prototype system for recommending cars.

Integrating collaborative filtering and matching-based search for product recommendations

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user’s query are retrieved and recommended. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of the products in which the target user’s neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAgQuery technique uses the attributes of the products that the user’s neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.

Lane filtering and situation awareness in motorcyclists : an on-road proof of concept study

In Victoria, as in other jurisdictions, there is very little research on the potential risks and benefits of lane filtering by motorcyclists, particularly from a road safety perspective. This on-road proof of concept study aimed to investigate whether and how lane filtering influences motorcycle rider situation awareness at intersections and to address factors that need to be considered for the design of a larger study in this area. Situation awareness refers to road users’ understanding of ‘what is going on’ around them and is a critical commodity for safe performance. Twenty-five experienced motorcyclists rode their own instrumented motorcycle around an urban test route in Melbourne whilst providing verbal protocols. Lane filtering occurred in 27% of 43 possible instances in which there were one or more vehicles in the traffic queue and the traffic lights were red on approach to the intersection. A network analysis procedure, based on the verbal protocols provided by motorcyclists, was used to identify differences in motorcyclist situation awareness between filtering and non-filtering events. Although similarities in situation awareness across filtering and nonfiltering motorcyclists were found, the analysis revealed some differences. For example, filtering motorcyclists placed more emphasis on the timing of the traffic light sequence and on their own actions when moving to the front of the traffic queue, whilst non-filtering motorcyclists paid greater attention to traffic moving through the intersection and approaching from behind. Based on the results of this study, the paper discusses some methodological and theoretical issues to be addressed in a larger study comparing situation awareness between filtering and non-filtering motorcyclists.

Pattern-based topic models for information filtering

Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, which has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering is rarely known. Patterns are always thought to be more representative than single terms for representing documents. In this paper, a novel information filtering model, Pattern-based Topic Model(PBTM) , is proposed to represent the text documents not only using the topic distributions at general level but also using semantic pattern representations at detailed specific level, both of which contribute to the accurate document representation and document relevance ranking. Extensive experiments are conducted to evaluate the effectiveness of PBTM by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model achieves outstanding performance.

The impact of risk-reducing hysterectomy and bilateral salpingo-oophorectomy on survival in patients with a history of breast cancer – a population-based data linkage study

Prophylactic surgery including hysterectomy and bilateral salpingo-oophorectomy (BSO) is recommended in BRCA positive women, while in women from the general population, hysterectomy plus BSO may increase the risk of overall mortality. The effect of hysterectomy plus BSO on women previously diagnosed with breast cancer is unknown. We used data from a population-base data linkage study of all women diagnosed with primary breast cancer in Queensland, Australia between 1997 and 2008 (n=21,067). We fitted flexible parametric breast cancer specific and overall survival models with 95% confidence intervals (also known as Royston-Parmar models) to assess the impact of risk-reducing surgery (removal of uterus, one or both ovaries). We also stratified analyses by age 20-49 and 50-79 years, respectively. Overall, 1,426 women (7%) underwent risk-reducing surgery (13% of premenopausal women and 3% of postmenopausal women). No women who had risk-reducing surgery, compared to 171 who did not have risk-reducing surgery developed a gynaecological cancer. Overall, 3,165 (15%) women died, including 2,195 (10%) from breast cancer. Hysterectomy plus BSO was associated with significantly reduced risk of death overall (adjusted HR = 0.69, 95% CI 0.53-0.89; P =0.005). Risk reduction was greater among premenopausal women, whose risk of death halved (HR, 0.45; 95% CI, 0.25-0.79; P < 0.006). This was largely driven by reduction in breast cancer-specific mortality (HR, 0.43; 95% CI, 0.24-0.79; P < 0.006). This population-based study found that risk-reducing surgery halved the mortality risk for premenopausal breast cancer patients. Replication of our results in independent cohorts, and subsequently randomised trials are needed to confirm these findings.

Pattern-based topics for document modelling in information filtering

Many mature term-based or pattern-based approaches have been used in the field of information filtering to generate users’ information needs from a collection of documents. A fundamental assumption for these approaches is that the documents in the collection are all about one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling, such as Latent Dirichlet Allocation (LDA), was proposed to generate statistical models to represent multiple topics in a collection of documents, and this has been widely utilized in the fields of machine learning and information retrieval, etc. But its effectiveness in information filtering has not been so well explored. Patterns are always thought to be more discriminative than single terms for describing documents. However, the enormous amount of discovered patterns hinder them from being effectively and efficiently used in real applications, therefore, selection of the most discriminative and representative patterns from the huge amount of discovered patterns becomes crucial. To deal with the above mentioned limitations and problems, in this paper, a novel information filtering model, Maximum matched Pattern-based Topic Model (MPBTM), is proposed. The main distinctive features of the proposed model include: (1) user information needs are generated in terms of multiple topics; (2) each topic is represented by patterns; (3) patterns are generated from topic models and are organized in terms of their statistical and taxonomic features, and; (4) the most discriminative and representative patterns, called Maximum Matched Patterns, are proposed to estimate the document relevance to the user’s information needs in order to filter out irrelevant documents. Extensive experiments are conducted to evaluate the effectiveness of the proposed model by using the TREC data collection Reuters Corpus Volume 1. The results show that the proposed model significantly outperforms both state-of-the-art term-based models and pattern-based models

A Guide to Applying Road Safety within a Workplace : A Bilateral Approach to Organisational Road Safety in Australia and New Zealand

Corporate and organisational fleet and road safety is of strong interest to government and government agencies in Australia and New Zealand. It has been identified that there is great opportunity to engage and assist organisations and corporations in the delivery of road safety and road safety measures to achieve nationally significant road related trauma reductions. This guide has therefore been developed through public sector funding for use by any workplace within Australia and New Zealand. Significant road safety benefits can be achieved by road safety government agencies (Australia and New Zealand) that engage with private and public sectors at their workplaces to address work related road safety issues. It has also been noted that organisational road safety advancement creates effective and sustainable outcomes, safer places of employment, and safer communities. This can be achieved without totally relying upon traditional and often lengthy processes such as further public legislation and/ or community attitudinal and behavioural change programs. Currently, there is little in the way of robust guides or support for those organisations that are wishing to adopt road safety within their places of employment, supply chain and/ or community. Due to this identified gap in available resource and support, it has been recommended that a practical organisational road safety guide be produced; hence the development of this guide. A guide, or supporting documentation, that bridges the gap between government and road safety research knowledge, internationally endorsed road safety methodology, and assists industry as the end user. To achieve this, the guide is designed to be non-specific to any industry sector and usable for small or large organisations, public or private, and engaging for senior executives and the personnel on the ground responsible for its implementation. Therefore, this guide is based on methodology and principles so that it can be applicable in a scalable way to the greatest number of public and private organisations while providing enough detail and ‘how to’ advice to enable organisations to generate their own solutions to road safety issues.

Kalman filtering for positioning and heading control of ships and offshore rigs

In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.

Assessing the bilateral geometrical differences of the tibia : are they the same?

Contralateral bones are often used in many medical applications but it is assumed that their bilateral differences are insignificant. Previous studies used a limited number of distance measurements in quantifying the corresponding differences; therefore, little is known about their bilateral 3D surface asymmetries. The aim of the study is to develop a comprehensive method to quantify geometrical asymmetries between the left and right tibia in order to provide first results on whether the contralateral tibia can be used as an equivalent reference. In this study, 3D bone models were reconstructed from CT scans of seven tibiae pairs, and 34 variables consisting of 2D and 3D measurements were measured from various anatomical regions. All 2D measurements, and lateral plateau and distal subchondral bone surface measurements showed insignificant differences (p > 0.05), but the rest of the surfaces showed significant differences (p < 0.05). Our results suggest that the contralateral tibia can be used as a reference especially in surgical applications such as articular reconstructions since the bilateral differences in the subchondral bone surfaces were less than 0.3 mm. The method can also be potentially transferable to other relevant studies that require the accurate quantification of bone bilateral asymmetries.

The impact of cataract surgery on vision-related quality of life for bilateral cataract patients in Ho Chi Minh City, Vietnam : a prospective study

Background To determine the impact of cataract surgery on vision-related quality of life (VRQOL) and examine the association between objective visual measures and change in VRQOL after surgery among bilateral cataract patients in Ho Chi Minh City, Vietnam. Methods A cohort of older patients with bilateral cataract was assessed one week before and one to three months after first eye or both eye cataract surgery. Visual measures including visual acuity, contrast sensitivity and stereopsis were obtained. Vision-related quality of life was assessed using the NEI VFQ-25. Descriptive analyses and a generalized linear estimating equation (GEE) analysis were undertaken to measure change in VRQOL after surgery. Results Four hundred and thirteen patients were assessed before cataract surgery and 247 completed the follow-up assessment one to three months after first or both eye cataract surgery. Overall, VRQOL significantly improved after cataract surgery (p < 0.001) particularly after both eye surgeries. Binocular contrast sensitivity (p < 0.001) and stereopsis (p < 0.001) were also associated with change in VRQOL after cataract surgery. Visual acuity was not associated with VRQOL. Conclusions Cataract surgery significantly improved VRQOL among bilateral cataract patients in Vietnam. Contrast sensitivity as well as stereopsis, rather than visual acuity significantly affected VRQOL after cataract surgery.

Prevalence and visual risk factors for falls in bilateral cataract patients in Ho Chi Minh City, Vietnam

Purpose To determine the prevalence of falls in the 12 months prior to cataract surgery and examine the associations between visual and other risk factors and falls among older bilateral cataract patients in Vietnam. Methods Data collected from 413 patients in the week before scheduled cataract surgery included a questionnaire and three objective visual tests. Results The outcome of interest was self-reported falls in the previous 12 months. A total of 13% (n = 53) of bilateral cataract patients reported 60 falls within the previous 12 months. After adjusting for age, sex, race, employment status, comorbidities, medication usage, refractive management, living status and the three objective visual tests in the worse eye, women (odds ratio, OR, 4.64, 95% confidence interval, CI, 1.85–11.66), and those who lived alone (OR 4.51, 95% CI 1.44–14.14) were at increased risk of a fall. Those who reported a comorbidity were at decreased risk of a fall (OR 0.43, 95% CI 0.19–0.95). Contrast sensitivity (OR 0.31, 95% CI 0.10–0.95) was the only significant visual test associated with a fall. These results were similar for the better eye, except the presence of a comorbidity was not significant (OR 0.45, 95% CI 0.20–1.02). Again, contrast sensitivity was the only significant visual factor associated with a fall (OR 0.15, 95% CI 0.04–0.53). Conclusion Bilateral cataract patients in Vietnam are potentially at high risk of falls and in need of falls prevention interventions. It may also be important for ophthalmologists and health professionals to consider contrast sensitivity measures when prioritizing cataract patients for surgery and assessing their risk of falls.

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Design of a nonlinear excitation controller using inverse filtering for transient stability enhancement

This paper proposes a nonlinear excitation controller to improve transient stability, oscillation damping and voltage regulation of the power system. The energy function of the predicted system states is used to obtain the desired flux for the next time step, which in turn is used to obtain a supplementary control input using an inverse filtering method. The inverse filtering technique enables the system to provide an additional input for the excitation system, which forces the system to track the desired flux. Synchronous generator flux saturation model is used in this paper. A single machine infinite bus (SMIB) test system is used to demonstrate the efficacy of the proposed control method using time-domain simulations. The robustness of the controller is assessed under different operating conditions.

A young immunocompetent patient with bilateral immune stromal keratitis due to varicella zoster and herpes simplex

This report describes the diagnostic features, clinical management and the issues associated with management of a young immunocompetent male who presented with a presumed left Herpes simplex immune stromal keratitis, and ten months later, a right immune stromal keratitis associated with Herpes zoster ophthalmicus.

Mechanical filtering for narrow-band hearing in the weta

This paper constitutes a major attempt to associate tympanic deflections with the mechanoreceptor organ location in an acoustic insect. The New Zealand tree weta (Hemideina thoracica) has tympanal ears located on each of the prothoracic tibiae. The tympana exhibit a sclerotized oval plate, membranous processes bulging out from the tibial cuticle and many loosely suspended ripples. We used microscanning laser Doppler vibrometry to determine how such a tympanal membrane vibrates in response to sound and whether the sclerotized region plays a role in hearing. The tympanum displays a single resonance at the calling frequency of the male, an unusual example of an insect tympana acting as a narrow bandpass filter. Both tympana resonate in phase with the stimulus and with each other. Histological sections show that the tympanal area is divided into two distinct regions, as in other ensiferans. An oval plate lies in the middle of a thickened region and is surrounded by a transparent and uniformly thin region. It is hinged dorsally to the tympanal rim and thus resembles the model of a ‘hinged flap’. The thickened region appears to act as a damping mass on the oscillation of the thin region, and vibration displacement is reduced in this area. The thinner area vibrates with higher amplitude, inducing mechanical pressure on the dorsal area adjacent to the crista acustica. We present a new model showing how the thickened region might confer a mechanical gain onto the activation of the crista acustica sensory neurons during the sound-induced oscillations.