Scale and Translation Invariant Collaborative Filtering Systems

Collaborative filtering systems are prediction algorithms over sparse data sets of user preferences. We modify a wide range of state-of-the-art collaborative filtering systems to make them scale and translation invariant and generally improve their accuracy without increasing their computational cost. Using the EachMovie and the Jester data sets, we show that learning-free constant time scale and translation invariant schemes outperforms other learning-free constant time schemes by at least 3% and perform as well as expensive memory-based schemes (within 4%). Over the Jester data set, we show that a scale and translation invariant Eigentaste algorithm outperforms Eigentaste 2.0 by 20%. These results suggest that scale and translation invariance is a desirable property.     

An Investigation of Textbook Vetting and Evaluation Process in Tanzania

Textbook vetting and evaluation process intends to ensure that the materials provided are relevant, of the required quality, suitable ad would enhance learning efficiency and effectiveness. The paper investigates the role of publishers and Tanzania Institute of Education (TIE) in the textbooks vetting and evaluation process; examines factors used to vet, evaluate and approve primary and secondary school textbooks in Tanzania and proposes Strategies that would enhance the textbook vetting, evaluation and process. The study used a mixed method research design. Respondents were selected educational publishers; MoEVT, Baraza la Kiswahili Tanzania, TIE, and Publishers Association of Tanzania. Questionnaire and semi- structured interview were used to collect data which were analysed qualitatively and quantitatively. Major findings of the study were; textbooks vetting and evaluation process is not professionally conducted although standard criteria have been established; there is not well established roles among key players involved in the vetting and evaluation process leading to conflict of interest between TIE and the publishers. The study recommends establishing an independent professional evaluation board and a well-defined timetable and effective communication among various players; enacting a book policy and adopting a limited multiple-textbook publishing system.     

Applying LDA Topic Modeling in Communication Research: Toward a Valid and Reliable Methodology

ABSTRACT

Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of topics to be generated; (c) evaluation of the model’s reliability; and (d) the process of validly interpreting the resulting topics. We review the research literature dealing with these questions and propose a methodology that approaches these challenges. Our overall goal is to make LDA topic modeling more accessible to communication researchers and to ensure compliance with disciplinary standards. Consequently, we develop a brief hands-on user guide for applying LDA topic modeling. We demonstrate the value of our approach with empirical data from an ongoing research project.     

Storytime with Fresh Professor,Part One

I wasn't always the Fresh Professor. At one point, I was just another starving actor, trying to make a living. But stories change over time, as do professional desires.     

Am I a Teaching Artist or an Administrator?

James Miles writes about his transition from teaching artist to administration. Is it for everyone?