Understanding a text requires two basic tasks: making inferences at several levels of knowledge and composing a global interpretation of the given text from those various types of inferences. Since making inferences at each level demands an extensive computations, there have been several attempts to use parallel inference mechanisms such as parallel marker passing (PMP) to increase the producti...

Consider users who share their data (e.g., location) with an untrusted service provider to obtain a personalized (e.g., location-based) service. Data obfuscation is a prevalent user-centric approach to protecting users’ privacy in such systems: the untrusted entity only receives a noisy version of user’s data. Perturbing data before sharing it, however, comes at the price of the users’ utility ...

To detect the small island effect (SIE) and nestedness patterns of herpetofauna of the West Indies, we derived and updated data on the presence/absence of herpetofauna in this region from recently published reviews. We applied regression-based analyses, including linear regression and piecewise regressions with two and three segments, to detect the SIE and then used the Akaike's information cri...

A first principal component combines several indicators so as to maximize their internal consistency for measuring a construct. First principal components are extracted here from Swiss Economic Institute and World Bank datasets containing yearly societal indicators for China. These indicators are input to population-weighted regressions without recourse to survey sampling or probabilistic infer...

We present some basic properties of two general graphical techniques for constructing views of high-dimensional objects, projection and section. Projections can easily display aspects of structure that are only of low dimension, while sections, i.e., intersections of subspaces with a highdimensional object, can easily display structure of only low codimension (and hence often high dimension). H...

The original idea of reasoning and control within fuzzy rule bases was proposed by Zadeh [1], and was called the Compositional Rule of Inference (CRI) and had the disadvantage of running directly in the k-dimensional input space (where k is the number of variables) while being able however to describe multi-dimensional membership function distributions of arbitrary shape. Its modified version, ...