Leveraging product adopter information from online reviews for product recommendation

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

Hybrid sampling on mutual information entropy-based clustering ensembles for optimizations

In this paper, we focus on the design of bivariate EDAs for discrete optimization problems and propose a new approach named HSMIEC. While the current EDAs require much time in the statistical learning process as the relationships among the variables are too complicated, we employ the Selfish gene theory (SG) in this approach, as well as a Mutual Information and Entropy based Cluster (MIEC) model is also set to optimize the probability distribution of the virtual population. This model uses a hybrid sampling method by considering both the clustering accuracy and clustering diversity and an incremental learning and resample scheme is also set to optimize the parameters of the correlations of the variables. Compared with several benchmark problems, our experimental results demonstrate that HSMIEC often performs better than some other EDAs, such as BMDA, COMIT, MIMIC and ECGA. © 2009 Elsevier B.V. All rights reserved.

The effect of mastery learning on a course in accounting information system (AIS): A comparison within public and private universities in Taiwan

The Accounting Information System (AIS) is an important course in the Department of Accounting (DoAc) of universities in Taiwan. This course is required for seniors not only because it meets the needs of the profession, but also because it provides continual study for the department's students.^ The scores of The National College and University Joint Entrance Examination (NUEE) show that students with high learning ability are admitted to public universities with high scores, while those with low learning ability are admitted only to private universities. The same situation has been found by the researcher while teaching an AIS course in DoAc of The Public Chun Shin University (CSU) and The Private Chinese Culture University (CCU).^ The purpose of this study was to determine whether low ability students enrolled in private universities in Taiwan in a mastery learning program could attain the same level as high ability students from public universities enrolled in a traditional program. An experimental design was used. The mastery learning method was used to teach three groups of seniors with low learning ability studying in the DoAc at CCU. The traditional method was used to teach the control group which consisted of senior students of DoAc of CSU with high learning ability. As a part of the mastery learning strategy, a formative test, quizzes, and homework were completed by the experimental group only, while the mid-term examination was completed by both groups as part of the course. The dependent variable was the summative test, the final examination. It was completed by both groups upon the course's completion.^ As predicted, there were significant differences between the two groups' results on the pretest. There were no significant differences between the two groups' results on the posttest. These findings support the hypothesis of the study and reveal the effectiveness of mastery learning strategies with low learning ability students. ^

The effects of using an alternative method for teaching badminton to post secondary level students in Taiwan

The effect of teaching method in physical education is an important issue and has been a concern of the expert teacher. Teachers are expected to create a model of teaching in their field; therefore, it is reasonable to question what is the effect of an alternative teaching method on student performance in physical education. This study explores whether teaching methods with advanced planning, behavior and belief in high enthusiasm, use of instructional strategies and evaluation, together termed a systematic teaching approach, used in a physical education activity would provide an effective environment for learning which supports student achievement in the psychomotor, cognitive, and affective domains. This study also investigated whether there was a difference in performance between students who were taught with a systematic teaching approach and students who were taught with the traditional teaching model. Information was collected using two performance skills, a written test, and one questionnaire. The 68 participants were randomly assigned into either an experimental group or a control group. Two teachers were assigned to either the experimental group or the control group. The teaching experiment took place at Tamsui Oxford University College in Taiwan and lasted eight weeks. ^ Research questions were analyzed using the t-test. Results indicated that a significant difference in students' performance was found between the experimental group and the control group on both the skill tests and the paper test. Analysis of student attitude toward their teacher and their course on the questionnaire indicated a significant difference between the experimental group and the control group. ^ The findings of this study imply that students who were taught with a systematic teaching style were significantly superior to students who were taught with the traditional model on these measures. This finding supports the contention that effective teaching in physical education is related to advanced planning, high enthusiasm, instructional strategy and evaluation and that all physical education teachers should implement these planning elements in the development of the teaching strategies. ^

A mixed method study of organizational culture dimensions of community college faculty library use and perceptions

Because past research has shown faculty as the driving force affecting student academic library use, librarians have tried for decades to engage classroom faculty in library activities. Nevertheless, a low rate of library use by faculty on behalf of their students persists. This study investigated the organizational culture dimensions affecting library faculty demand at a community college. The study employed a sequential quantitative-qualitative research design. A random sample of full-time faculty at a large urban community college responded to a 46-item survey. The survey data showed strong espoused support (84%) for the use of library-based materials but a much lower incidence of putting this construct into practice (46%). Interviews were conducted with 11 full-time faculty from two academic groups, English-Humanities and Engineering-Math-Science. These groups were selected because the survey data resulted in statistically significant differences between the groups pertaining to several key variables. These variables concerned the professors' perceptions of the importance of library research in their discipline, the amount of time spent on the course textbook during a term, the frequency of conversations about the library in the academic department, and the professors' ratings of the librarians' skill in instruction related to the academic discipline. All interviewees described the student culture as the predominant organizational culture at Major College. Although most interview subjects held to high information literacy standards in their courses, others were less convinced these could be realistically practiced, based on a perception of students' poor academic skills, lack of time for students to complete assignments due to their commuter and family responsibilities, and the need to focus on textbook content. Recommended future research would involve investigation of methods to bridge the gap between high espoused value toward information literacy and implementation of information-literate coursework.

Efficient storage and domain-specific information discovery on semistructured documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^

Mitigating congestion by integrating time forecasting and realtime information aggregation in cellular networks

An iterative travel time forecasting scheme, named the Advanced Multilane Prediction based Real-time Fastest Path (AMPRFP) algorithm, is presented in this dissertation. This scheme is derived from the conventional kernel estimator based prediction model by the association of real-time nonlinear impacts that caused by neighboring arcs’ traffic patterns with the historical traffic behaviors. The AMPRFP algorithm is evaluated by prediction of the travel time of congested arcs in the urban area of Jacksonville City. Experiment results illustrate that the proposed scheme is able to significantly reduce both the relative mean error (RME) and the root-mean-squared error (RMSE) of the predicted travel time. To obtain high quality real-time traffic information, which is essential to the performance of the AMPRFP algorithm, a data clean scheme enhanced empirical learning (DCSEEL) algorithm is also introduced. This novel method investigates the correlation between distance and direction in the geometrical map, which is not considered in existing fingerprint localization methods. Specifically, empirical learning methods are applied to minimize the error that exists in the estimated distance. A direction filter is developed to clean joints that have negative influence to the localization accuracy. Synthetic experiments in urban, suburban and rural environments are designed to evaluate the performance of DCSEEL algorithm in determining the cellular probe’s position. The results show that the cellular probe’s localization accuracy can be notably improved by the DCSEEL algorithm. Additionally, a new fast correlation technique for overcoming the time efficiency problem of the existing correlation algorithm based floating car data (FCD) technique is developed. The matching process is transformed into a 1-dimensional (1-D) curve matching problem and the Fast Normalized Cross-Correlation (FNCC) algorithm is introduced to supersede the Pearson product Moment Correlation Co-efficient (PMCC) algorithm in order to achieve the real-time requirement of the FCD method. The fast correlation technique shows a significant improvement in reducing the computational cost without affecting the accuracy of the matching process.

A theory of constraints service systems improvement method: Case of the airline turnaround problem

This dissertation develops a process improvement method for service operations based on the Theory of Constraints (TOC), a management philosophy that has been shown to be effective in manufacturing for decreasing WIP and improving throughput. While TOC has enjoyed much attention and success in the manufacturing arena, its application to services in general has been limited. The contribution to industry and knowledge is a method for improving global performance measures based on TOC principles. The method proposed in this dissertation will be tested using discrete event simulation based on the scenario of the service factory of airline turnaround operations. To evaluate the method, a simulation model of aircraft turn operations of a U.S. based carrier was made and validated using actual data from airline operations. The model was then adjusted to reflect an application of the Theory of Constraints for determining how to deploy the scarce resource of ramp workers. The results indicate that, given slight modifications to TOC terminology and the development of a method for constraint identification, the Theory of Constraints can be applied with success to services. Bottlenecks in services must be defined as those processes for which the process rates and amount of work remaining are such that completing the process will not be possible without an increase in the process rate. The bottleneck ratio is used to determine to what degree a process is a constraint. Simulation results also suggest that redefining performance measures to reflect a global business perspective of reducing costs related to specific flights versus the operational local optimum approach of turning all aircraft quickly results in significant savings to the company. Savings to the annual operating costs of the airline were simulated to equal 30% of possible current expenses for misconnecting passengers with a modest increase in utilization of the workers through a more efficient heuristic of deploying them to the highest priority tasks. This dissertation contributes to the literature on service operations by describing a dynamic, adaptive dispatch approach to manage service factory operations similar to airline turnaround operations using the management philosophy of the Theory of Constraints.

A multi-method approach for the assessment of composite indices and rankings

There is growing popularity in the use of composite indices and rankings for cross-organizational benchmarking. However, little attention has been paid to alternative methods and procedures for the computation of these indices and how the use of such methods may impact the resulting indices and rankings. This dissertation developed an approach for assessing composite indices and rankings based on the integration of a number of methods for aggregation, data transformation and attribute weighting involved in their computation. The integrated model developed is based on the simulation of composite indices using methods and procedures proposed in the area of multi-criteria decision making (MCDM) and knowledge discovery in databases (KDD). The approach developed in this dissertation was automated through an IT artifact that was designed, developed and evaluated based on the framework and guidelines of the design science paradigm of information systems research. This artifact dynamically generates multiple versions of indices and rankings by considering different methodological scenarios according to user specified parameters. The computerized implementation was done in Visual Basic for Excel 2007. Using different performance measures, the artifact produces a number of excel outputs for the comparison and assessment of the indices and rankings. In order to evaluate the efficacy of the artifact and its underlying approach, a full empirical analysis was conducted using the World Bank's Doing Business database for the year 2010, which includes ten sub-indices (each corresponding to different areas of the business environment and regulation) for 183 countries. The output results, which were obtained using 115 methodological scenarios for the assessment of this index and its ten sub-indices, indicated that the variability of the component indicators considered in each case influenced the sensitivity of the rankings to the methodological choices. Overall, the results of our multi-method assessment were consistent with the World Bank rankings except in cases where the indices involved cost indicators measured in per capita income which yielded more sensitive results. Low income level countries exhibited more sensitivity in their rankings and less agreement between the benchmark rankings and our multi-method based rankings than higher income country groups.

Integrated construction project delivery system in the U.S. public sector: An information modeling framework

Integrated project delivery (IPD) method has recently emerged as an alternative to traditional delivery methods. It has the potential to overcome inefficiencies of traditional delivery methods by enhancing collaboration among project participants. Information and communication technology (ICT) facilitates IPD by effective management, processing and communication of information within and among organizations. While the benefits of IPD, and the role of ICT in realizing them, have been generally acknowledged, the US public construction sector is very slow in adopting IPD. The reasons are - lack of experience and inadequate understanding of IPD in public owner as confirmed by the results of the questionnaire survey conducted under this research study. The public construction sector should be aware of the value of IPD and should know the essentials for effective implementation of IPD principles - especially, they should be cognizant of the opportunities offered by advancements in ICT to realize this.^ In order to address the need an IPD Readiness Assessment Model (IPD-RAM) was developed in this research study. The model was designed with a goal to determine IPD readiness of a public owner organization considering selected IPD principles, and ICT levels, at which project functions were carried out. Subsequent analysis led to identification of possible improvements in ICTs that have the potential to increase IPD readiness scores. Termed as the gap identification, this process was used to formulate improvement strategies. The model had been applied to six Florida International University (FIU) construction projects (case studies). The results showed that the IPD readiness of the organization was considerably low and several project functions can be improved by using higher and/or advanced level ICT tools and methods. Feedbacks from a focus group comprised of FIU officials and an independent group of experts had been received at various stages of this research and had been utilized during development and implementation of the model. Focus group input was also helpful for validation of the model and its results. It was hoped that the model developed would be useful to construction owner organizations in order to assess their IPD readiness and to identify appropriate ICT improvement strategies.^

Efficient Storage and Domain-Specific Information Discovery on Semistructured Documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model's parsing mechanism. The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents.

An automatic method of above-water iceberg 3-D profiling based on autonomous surface craft (ASC) using surface images and LIDAR

This thesis reports on a novel method to build a 3-D model of the above-water portion of icebergs using surface imaging. The goal is to work towards the automation of iceberg surveys, allowing an Autonomous Surface Craft (ASC) to acquire shape and size information. After collecting data and images, the core software algorithm is made up of three parts: occluding contour finding, volume intersection, and parameter estimation. A software module is designed that could be used on the ASC to perform automatic and fast processing of above-water surface image data to determine iceberg shape and size measurement and determination. The resolution of the method is calculated using data from the iceberg database of the Program of Energy Research and Development (PERD). The method was investigated using data from field trials conducted through the summer of 2014 by surveying 8 icebergs during 3 expeditions. The results were analyzed to determine iceberg characteristics. Limitations of this method are addressed including its accuracy. Surface imaging system and LIDAR system are developed to profile the above-water iceberg in 2015.

Patient/carers' recollection of medicines related information from an out-patient clinic appointment

AIM: To identify what medicines related information children/young people or their parents/carers are able to recall following an out-patient clinic appointment. METHOD: A convenience sample of patients' prescribed at least one new long-term (>6 weeks) medicine were recruited from a single UK paediatric hospital out-patient pharmacy. A face-to-face semi-structured questionnaire was administered to participants when they presented with their prescription. The questionnaire included the following themes: names of the medicines, therapeutic indication, dose regimen, duration of treatment and adverse effects.The results were analysed using Microsoft Excel 2013. RESULTS: One hundred participants consented and were included in the study. One hundred and forty-five medicines were prescribed in total. Participants were able to recall the names of 96 (66%) medicines and were aware of the therapeutic indication for 142 (97.9%) medicines. The dose regimen was accurately described for 120 (82.8%) medicines with the duration of treatment known for 132 (91%). Participants mentioned that they had been advised about side effects for 44 (30.3%) medicines. Specific counselling points recommended by the BNFc1, were either omitted or not recalled by participants for the following systemic treatments: cetirizine (1), chlorphenamine (1), desmopressin (2), hydroxyzine (2), itraconazole (1), piroxicam (2), methotrexate (1), stiripentol (1) and topiramate (1). CONCLUSION: Following an out-patient consultation, where a new medicine is prescribed, children and their parents/carers are usually able to recall the indication, dose regimen and duration of treatment. Few were able to recall, or were told about, possible adverse effects. This may include some important drug specific effects that require vigilance during treatment.Patients, along with families and carers, should be involved in the decision to prescribe a medicine.2 This includes a discussion about the benefits of the medicine on the patient's condition and possible adverse effects.2 Treatment side effects have been shown to be a factor in treatment non-adherence in paediatric long-term medical conditions.3 Practitioners should explain to patients, and their family members or carers where appropriate, how to identify and report medicines-related patient safety incidents.4 However, this study suggests that medical staff may not be comfortable discussing the adverse effects of medicines with patients or their parents/carers.Further research in to the shared decision making process in the paediatric out-patient clinic when a new long-term medicine is prescribed is required to further support medicines adherence and the patient safety agenda.