Language Modelling (LM) and TF-IDF are two retrieval models with different foundations. There have been efforts aiming at establishing the relationship between these models, and whether one includes the other. Whether their combination could yield a third and better model is an open research question. This paper revisits the foundations of LM and TF-IDF and explores how these models’ bare struc...

Integer-Controlled Dataflow (IDF) and its code generation applications in Ptolemy are presented. In IDF graphs, which specify data processing systems, data token flow is controlled by integer control tokens and states of actors at run-time. The firing order of actors (schedule) is determined at compile-time, however, the actors are conditionally activated at run-time. This static schedule contr...

IDF is an Incremental Development Framework which supports the development and the verification of UML models for reactive systems. IDF offers refinement and extension techniques allowing liveness properties to be preserved during the model developments. Here, we improve the framework in order to analyze models from a safety point of view. For this purpose, we associate IDF with the experienced...

The Dirichlet compound multinomial (DCM) distribution has recently been shown to be a good model for documents because it captures the phenomenon of word burstiness, unlike standard models such as the multinomial distribution. This paper investigates the DCM Fisher kernel, a function for comparing documents derived from the DCM. We show that the DCM Fisher kernel has components that are similar...

Inverse document frequency (IDF) is one of the most useful and widely used concepts in information retrieval. When it is used in combination with the term frequency (TF), the result is a very effective term weighting scheme (TF-IDF) that has been applied in information retrieval to determine the weight of the terms. Terms with high TF-IDF values imply a strong relationship with the document the...

Metabolic syndrome (MetS) is a steering force for the cardiovascular diseases epidemic in Asia. This study aimed to compare the prevalence of MetS in Malaysian adults using NCEP-ATP III, IDF, and JIS definitions, identify the demographic factors associated with MetS, and determine the level of agreement between these definitions. The analytic sample consisted of 8,836 adults aged ≥30 years recr...

This paper describes an adapatation of the tf-idf model to Japanese graphemephoneme alignment, without reliance on training data. The tf-idf model is optionally complemented with affixation and conjugation handling modules, and determines frequencies through analysis of “alignment potential”. The proposed system achieved a maximum accuracy of 94.74% on evaluation.

In this abstract, we propose several computational approaches for clustering scRNA-Seq data based on the Term Frequency Inverse Document Frequency (TF-IDF) transformation that has been successfully used in the field of text analysis. Empirical evaluation on simulated cell mixtures with different levels of complexity suggests that the TF-IDF methods consistently outperform existing scRNA-Seq clu...

OBJECTIVE The metabolic syndrome (MS) is a cluster of cardiometabolic factors, which predisposes to diabetes and cardiovascular disease (CVD). Early detection of high-risk individuals for MS using accurate measures of insulin resistance (IR) could improve detection and prevention of CVD and diabetes. The aim of this study was to explore the ability of lipid accumulation product (LAP), compared ...

BACKGROUND Metabolic syndrome(MetS) is an aggregation of multiple metabolic risk factors shown to lead to the development of cardiovascular disease. The International Diabetes Federation(IDF) and the modified National Cholesterol Education Program Adult Treatment Panel Ⅲ(mNCEP) criteria are used in identifying MetS. This report will determine the prevalence of MetS and its component risk factor...