Counting inversions is a classic and important problem in databases. The number of inversions, K∗, in a list L = (L(1), L(2), . . . , L(n)) is defined as the number of pairs i < j with L(i) > L(j). In this paper, new results for this problem are presented: 1. In the I/O-model, an adaptive algorithm is presented for calculating K∗. The algorithm performs O( B + N B logM/B( K∗ NB )) I/Os. When K∗...

This paper introduces a new similarity measure based on edge counting in a taxonomy like WorldNet or Ontology. Measurement of similarity between text segments or concepts is very useful for many applications like information retrieval, ontology matching, text mining, and question answering and so on. Several measures have been developed for measuring similarity between two concepts: out of thes...

A major benefit of graphical models is that most knowledge is captured in the model structure. Many models, however, produce inference problems with a lot of symmetries not reflected in the graphical structure and hence not exploitable by efficient inference techniques such as belief propagation (BP). In this paper, we present a new and simple BP algorithm, called counting BP, that exploits suc...

Lifted inference algorithms exploit repeated structure in probabilistic models to answer queries efficiently. Previous work such as de Salvo Braz et al.’s first-order variable elimination (FOVE) has focused on the sharing of potentials across interchangeable random variables. In this paper, we also exploit interchangeability within individual potentials by introducing counting formulas, which i...