There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

Combinatorial scientific computing plays an important enabling role in computational science, particularly in high performance scientific computing. In this thesis, we will describe our work on optimizing matrix-vector multiplication using combinatorial techniques. Our research has focused on two different problems in combinatorial scientific…

Concepts behind plausible values in estimating population characteristics from sparse matrix samples of item responses are discussed. The use of marginal analyses is described in the context of the National Assessment of Educational Progress, and the approach is illustrated with Scholastic Aptitude Test data for 9,075 high school seniors. (SLD)

We describe a data mining pipeline to convert data from educational systems into knowledge component (KC) models. In contrast to other approaches, our approach employs and compares multiple model search methodologies (e.g., sparse factor analysis, covariance clustering) within a single pipeline. In this preliminary work, we describe our approach's…

Although the Japanese reflexive "zibun" can be bound both locally and across clause boundaries, the third-person pronoun "kare" cannot take a local antecedent. These are properties that children need to learn about their language, but we show that the direct evidence of the binding possibilities of "zibun" is sparse…

To contribute to the sparse educational research on student understanding of eigenspace, we investigated how students reason about linear combinations of eigenvectors. We present results from student reasoning on two written multiple-choice questions with open-ended justifications involving linear combinations of eigenvectors in which the…

Nudging is one of the strategies from behavioral economics that aims to influence behavior by changing the environment. We propose that it could also be a valuable means to influence behavior in educational contexts. However, implementation of nudging in education is yet sparse. We describe the relevant issues to consider when applying nudging in…

Purpose: Family support programs commonly use self-sufficiency matrices (SSMs) to measure family outcomes, however, validation research on SSMs is sparse. This study examined the reliability of the Colorado Family Support Assessment 2.0 (CFSA 2.0) to measure family self-reliance across 14 domains (e.g., employment). Methods: Ten written case…

The generalized partial-credit model (GPCM) is used frequently in educational testing and in large-scale assessments for analyzing polytomous data. Special cases of the generalized partial-credit model are the partial-credit model--or Rasch model for ordinal data--and the two parameter logistic (2PL) model. This article extends the GPCM to the…

More than a dozen statistical models have been developed for the purpose of cognitive diagnosis. These models are supposed to extract a much finer level of information from item responses than traditional unidimensional item response models. In this paper, a general diagnostic model (GDM) was used to analyze a set of simulated sparse data and real…

The central goals of most introductory linear algebra courses are to develop students' proficiency with matrix techniques, to promote their understanding of key concepts, and to increase their ability to make connections between concepts. In this article, we present an innovative method using adjacency matrices to analyze students' interpretation…

The goal of this work is to enhance the robustness and efficiency of the multimodal human states recognition task. Human states recognition can be considered as a joint term for identifying/verifing various kinds of human related states, such as biometric identity, language spoken, age, gender, emotion, intoxication level, physical activity, vocal…

Language modeling is one of many problems in language processing that have to grapple with naturally high ambient dimensions. Even in large datasets, the number of unseen sequences is overwhelmingly larger than the number of observed ones, posing clear challenges for estimation. Although existing methods for building smooth language models tend to…

While tonal systems have typically been classified as "pitch accent" or "true tonal", there is growing evidence that systems instead have a variety of features which vary across languages, rather than falling into discrete categories. These category labels have been used widely in literature about the languages of New Guinea,…

It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2] and the likelihood ratio statistic G[superscript…