Predicting Multi-class Customer Profiles Based on Transactions: a Case Study in Food Sales

Predicting the class of a customer profile is a key task in marketing, which enables businesses to approach the right customer with the right product at the right time through the right channel to satisfy the customer's evolving needs. However, due to costs, privacy and/or data protection, only the business' owned transactional data is typically available for constructing customer profiles. Predicting the class of customer profiles based on such data is challenging, as the data tends to be very large, heavily sparse and highly skewed. We present a new approach that is designed to efficiently and accurately handle the multi-class classification of customer profiles built using sparse and skewed transactional data. Our approach first bins the customer profiles on the basis of the number of items transacted. The discovered bins are then partitioned and prototypes within each of the discovered bins selected to build the multi-class classifier models. The results obtained from using four multi-class classifiers on real-world transactional data from the food sales domain consistently show the critical numbers of items at which the predictive performance of customer profiles can be substantially improved

Reducing Spatial Data Complexity for Classification Models

Intelligent data analytics gradually becomes a day-to-day reality of today's businesses. However, despite rapidly increasing storage and computational power current state-of-the-art predictive models still can not handle massive and noisy corporate data warehouses. What is more adaptive and real-time operational environment requires multiple models to be frequently retrained which fiirther hinders their use. Various data reduction techniques ranging from data sampling up to density retention models attempt to address this challenge by capturing a summarised data structure, yet they either do not account for labelled data or degrade the classification performance of the model trained on the condensed dataset. Our response is a proposition of a new general framework for reducing the complexity of labelled data by means of controlled spatial redistribution of class densities in the input space. On the example of Parzen Labelled Data Compressor (PLDC) we demonstrate a simulatory data condensation process directly inspired by the electrostatic field interaction where the data are moved and merged following the attracting and repelling interactions with the other labelled data. The process is controlled by the class density function built on the original data that acts as a class-sensitive potential field ensuring preservation of the original class density distributions, yet allowing data to rearrange and merge joining together their soft class partitions. As a result we achieved a model that reduces the labelled datasets much further than any competitive approaches yet with the maximum retention of the original class densities and hence the classification performance. PLDC leaves the reduced dataset with the soft accumulative class weights allowing for efficient online updates and as shown in a series of experiments if coupled with Parzen Density Classifier (PDC) significantly outperforms competitive data condensation methods in terms of classification performance at the comparable compression levels

Unsupervised Ensembles Techniques for Visualization

In this paper we introduce two unsupervised techniques for visualization purposes based on the use of ensemble methods. The unsupervised techniques which are often quite sensitive to the presence of outliers are combined with the ensemble approaches in order to overcome the influence of outliers. The first technique is based on the use of Principal Component Analysis and the second one is known for its topology preserving characteristics and is based on the combination of the Scale Invariant Map and Maximum Likelihood Hebbian learning. In order to show the advantage of these novel ensemble-based techniques the results of some experiments carried out on artificial and real data sets are included

Area-level and individual correlates of active transportation among adults in Germany: A population-based multilevel study

This study aimed at estimating the prevalence in adults of complying with the aerobic physical activity (PA) recommendation through transportation-related walking and cycling. Furthermore, potential determinants of transportation-related PA recommendation compliance were investigated. 10,872 men and 13,144 women aged 18 years or older participated in the cross-sectional 'German Health Update 2014/15 - EHIS' in Germany. Transportation-related walking and cycling were assessed using the European Health Interview Survey-Physical Activity Questionnaire. Three outcome indicators were constructed: walking, cycling, and total active transportation (>= 600 metabolic equivalent, MET-min/week). Associations were analyzed using multilevel regression analysis. Forty-two percent of men and 39% of women achieved >= 600 MET-min/week with total active transportation. The corresponding percentages for walking were 27% and 28% and for cycling 17% and 13%, respectively. Higher population density, older age, lower income, higher work-related and leisure-time PA, not being obese, and better self-perceived health were positively associated with transportation-related walking and cycling and total active transportation among both men and women. The promotion of walking and cycling among inactive people has great potential to increase PA in the general adult population and to comply with PA recommendations. Several correlates of active transportation were identified which should be considered when planning public health policies and interventions

Epitaxy: Programmable Atom Equivalents

The programmability of DNA makes it an attractive structure-directing ligand for the assembly of nanoparticle (NP) superlattices in a manner that mimics many aspects of atomic crystallization. However, the synthesis of multilayer single crystals of defined size remains a challenge. Though previous studies considered lattice mismatch as the major limiting factor for multilayer assembly, thin film growth depends on many interlinked variables. Here, a more comprehensive approach is taken to study fundamental elements, such as the growth temperature and the thermodynamics of interfacial energetics, to achieve epitaxial growth of NP thin films. Both surface morphology and internal thin film structure are examined to provide an understanding of particle attachment and reorganization during growth. Under equilibrium conditions, single crystalline, multilayer thin films can be synthesized over 500 × 500 μm² areas on lithographically patterned templates, whereas deposition under kinetic conditions leads to the rapid growth of glassy films. Importantly, these superlattices follow the same patterns of crystal growth demonstrated in atomic thin film deposition, allowing these processes to be understood in the context of well-studied atomic epitaxy and enabling a nanoscale model to study fundamental crystallization processes. Through understanding the role of epitaxy as a driving force for NP assembly, we are able to realize 3D architectures of arbitrary domain geometry and size.United States. Air Force Office of Scientific Research (AFOSR FA9550-11-1-0275)United States. Air Force Office of Scientific Research (FA9550-12-1-0280)United States. Department of Defense (N00014-15-1-0043)United States. Department of Energy (Grant DE-SC0000989-0002)National Science Foundation (U.S.) (Award DMR-1121262

A linguistic analysis of lying in negative evaluations: The speech act performance of Chinese learners of Korean

이 논문은 중국인 한국어 학습자와 한국어 화자들 사이의 ‘거짓말’ 화행 양상을 언어학적으로 분석한 연구이다. 여기서 말하는 ‘거짓말’이란 요청, 사과, 거절 등과 같은 화행의 일종으로서 ‘부정적 평가’에 속하며 대화 참여자나 상황을 고려한 소위 ‘선의의 거짓말’을 가리키는 것으로 이해할 수 있을 것이다. 우리는 중국인 한국어 학습자 15명과 한국어 화자 15명을 대상으로 담화완성테스트(DCT)와 부연설명질문지(QFE)를 사용하여 피실험자들의 화행을 분석하였다. 피실험자 자신들의 설명과 한국어교육 전문가 다섯 명의 판정을 종합해 ‘거짓말’ 화행을 가려내고 통계 처리를 바탕으로 다음과 같은 결론에 도달했다. 한국어 화자들이 중국인 한국어 학습자들보다 (선의의) 거짓말을 더 많이 수행하는 것으로 나타났다. 그리고 두 집단 모두 부정적 평가가 사물에 관련된 경우보다 사람에 관련된 경우에 ‘거짓말’ 화행을 더 많이 사용한다. 그러나 화자와 청자 사이의 친소관계(distance)나 상하관계(power)는 거짓말 사용에 직접적 상관 관계를 보여주지 않았다. 이 연구는 지금까지 화행 연구 중에서 상대적으로 연구가 부진했던 부정평가와 ‘거짓말’ 화행에 대한 분석을 시도했다는 점에서 의미가 있다. 또한 한국어 화자와 중국인 한국어 학습자 사이에 보이는 화행 수행의 차이를 문화인식(cultural awareness)의 관점에서 해석해 볼 수 있는 가능성도 열어 주었다

Outlier Resistant PCA Ensembles

Statistical re-sampling techniques have been used extensively and successfully in the machine learning approaches for generation of classifier and predictor ensembles. It has been frequently shown that combining so called unstable predictors has a stabilizing effect on and improves the performance of the prediction system generated in this way. In this paper we use the re-sampling techniques in the context of Principal Component Analysis (PCA). We show that the proposed PCA ensembles exhibit a much more robust behaviour in the presence of outliers which can seriously affect the performance of an individual PCA algorithm. The performance and characteristics of the proposed approaches are illustrated on a number of experimental studies where an individual PCA is compared to the introduced PCA ensemble

Epitaxy: Programmable Atom Equivalents Versus Atoms

The programmability of DNA makes it an attractive structure-directing ligand for the assembly of nanoparticle (NP) superlattices in a manner that mimics many aspects of atomic crystallization. However, the synthesis of multilayer single crystals of defined size remains a challenge. Though previous studies considered lattice mismatch as the major limiting factor for multilayer assembly, thin film growth depends on many interlinked variables. Here, a more comprehensive approach is taken to study fundamental elements, such as the growth temperature and the thermodynamics of interfacial energetics, to achieve epitaxial growth of NP thin films. Both surface morphology and internal thin film structure are examined to provide an understanding of particle attachment and reorganization during growth. Under equilibrium conditions, single crystalline, multilayer thin films can be synthesized over 500 × 500 μm2 areas on lithographically patterned templates, whereas deposition under kinetic conditions leads to the rapid growth of glassy films. Importantly, these superlattices follow the same patterns of crystal growth demonstrated in atomic thin film deposition, allowing these processes to be understood in the context of well-studied atomic epitaxy and enabling a nanoscale model to study fundamental crystallization processes. Through understanding the role of epitaxy as a driving force for NP assembly, we are able to realize 3D architectures of arbitrary domain geometry and size

Epitaxy: Programmable Atom Equivalents Versus Atoms

The programmability of DNA makes it an attractive structure-directing ligand for the assembly of nanoparticle (NP) superlattices in a manner that mimics many aspects of atomic crystallization. However, the synthesis of multilayer single crystals of defined size remains a challenge. Though previous studies considered lattice mismatch as the major limiting factor for multilayer assembly, thin film growth depends on many interlinked variables. Here, a more comprehensive approach is taken to study fundamental elements, such as the growth temperature and the thermodynamics of interfacial energetics, to achieve epitaxial growth of NP thin films. Both surface morphology and internal thin film structure are examined to provide an understanding of particle attachment and reorganization during growth. Under equilibrium conditions, single crystalline, multilayer thin films can be synthesized over 500 × 500 μm2 areas on lithographically patterned templates, whereas deposition under kinetic conditions leads to the rapid growth of glassy films. Importantly, these superlattices follow the same patterns of crystal growth demonstrated in atomic thin film deposition, allowing these processes to be understood in the context of well-studied atomic epitaxy and enabling a nanoscale model to study fundamental crystallization processes. Through understanding the role of epitaxy as a driving force for NP assembly, we are able to realize 3D architectures of arbitrary domain geometry and size

The branded and gendered Brazilian body: Material and symbolic constructions in an overlooked context

Since its first conference in 2006, CCT has been growing in size and reach. Some have noted that CCT has become much more European in the recent years, with North American and European countries taking turns to host the event