We should not have to look at the entire corpus (e.g., the Web) to know if two (or more) words are strongly associated or not. One can often obtain estimates of associations from a small sample. We develop a sketch-based algorithm that constructs a contingency table for a sample. One can estimate the contingency table for the entire population using straightforward scaling. However, one can do ...

Extending the notion of indispensable binomials of a toric ideal ([14], [7]), we define indispensable monomials of a toric ideal and establish some of their properties. They are useful for searching indispensable binomials of a toric ideal and for proving the existence or non-existence of a unique minimal system of binomials generators of a toric ideal. Some examples of indispensable monomials ...

We propose a strategy for disclosure risk evaluation and disclosure control of a microdata set based on fitting decomposable models of a multiway contingency table corresponding to the microdata set. By fitting decomposable models, we can evaluate per-record identification (or re-identification) risk of a microdata set. Furthermore we can easily determine swappability of risky records which doe...

The Goodman–Kruskal measure, which is a well-known measure of dependence for contingency tables, is generalized to the case when the variables of interest are categorized by linguistic terms rather than crisp sets. In addition, to test the hypothesis of independence in such contingency tables, a novel method of decision making is developed based on a concept of fuzzy p-value. The applicability ...

The diversity of housing-unit supply in suburban areas has been a central concern for planners and policy makers for at least 50 years. Absence of census crosstabulation data on housing unit structure-type by unit-size (number of bedrooms), has limited our understanding of the historical and regional evolution of relative suburban housing-unit diversity. I use census microdata to estimate measu...

A new datamining procedure called KL–Miner is presented. The procedure mines for various patterns based on evaluation of two–dimensional contingency tables, including patterns of statistical nature. The procedure is a result of continued development of the academic LISp-Miner system for KDD.

Data continuously stream into our minds, guiding our learning and inference with no trial delimiters to parse our experience. These data can take on a variety of forms, but research on causal learning has emphasized discrete contingency data over continuous sequences of events. We present a formal framework for modeling causal inferences about sequences of point events, based on Bayesian infere...

Simple algorithms for probabilistic inversion are proposed, based on iterative sample re-weighting. One of these, iterative proportional fitting (IP F), dates from the 1930's and has been studied extensively with regard to contingency tables. A new algorithm is shown to converge even when IP F is infeasible.

A method is proposed for the detection of item bias with respect to observed or unobserved subgroups. The method uses quasi-loglinear models for the incomplete subgroup x testscore x item 1 x x itek k contingency table. If subgroup membership is unknown the models are Haberman's incomplete-latent-class models. The (conditional) Rasch model is formulated as a quasi-loglinear model. The parameter...

Lienert (1969, 1971a) justified his invention of Configural Frequency Analysis (CFA) by the observation that higher-order interactions may exist in threeand higher-dimensional data even if no correlations between any pairs of variables can be observed. In Lienert (1971b) Hierarchical CFA (HCFA) was proposed in order to find that subset of variables which shows the highest degree of interdepende...