Tuple

About: Tuple is a research topic. Over the lifetime, 6513 publications have been published within this topic receiving 146057 citations. The topic is also known as: tuple & ordered tuplet.

Method of calculating tuples for data cubes

Abstract: A method and apparatus of calculating data cubes is shown in which a data set is partitioned into memory sized data fragments and cuboid tuples are calculated from the data fragments A search lattice of the data cube is used as a basis for ordering calculations of lower dimensional cuboids in the data cube Identification of a minimum number of paths through the lattice that is sufficient to traverse all nodes in the lattice is achieved by iteratively duplicating twice all paths in a lower dimensional space, distributing a new attribute to the first duplicate, moving end points from paths of the second duplicate to a corresponding path in the first duplicate and merging the first and second duplicates

Stochastic Relational Models for Discriminative Link Prediction

Abstract: We introduce a Gaussian process (GP) framework, stochastic relational models (SRM), for learning social, physical, and other relational phenomena where interactions between entities are observed. The key idea is to model the stochastic structure of entity relationships (i.e., links) via a tensor interaction of multiple GPs, each defined on one type of entities. These models in fact define a set of nonparametric priors on infinite dimensional tensor matrices, where each element represents a relationship between a tuple of entities. By maximizing the marginalized likelihood, information is exchanged between the participating GPs through the entire relational network, so that the dependency structure of links is messaged to the dependency of entities, reflected by the adapted GP kernels. The framework offers a discriminative approach to link prediction, namely, predicting the existences, strengths, or types of relationships based on the partially observed linkage network as well as the attributes of entities (if given). We discuss properties and variants of SRM and derive an efficient learning algorithm. Very encouraging experimental results are achieved on a toy problem and a user-movie preference link prediction task. In the end we discuss extensions of SRM to general relational learning tasks.

Resource access and mobility control with dynamic privileges acquisition

Abstract: µKlaim is a process language that permits programming distributed systems made up of several mobile components interacting through multiple distributed tuple spaces. We present the language and a type system for controlling the activities, e.g. access to resources and mobility, of the processes in a net. By dealing with privileges acquisition, the type system enables dynamic variations of security policies. We exploit a combination of static and dynamic type checking, and of inlined reference monitoring, to guarantee absence of run-time errors due to lack of privileges and state two type soundness results: one involves whole nets, the other is relative to subnets of larger nets.

HoTTSQL: proving query rewrites with univalent SQL semantics

Abstract: Every database system contains a query optimizer that performs query rewrites. Unfortunately, developing query optimizers remains a highly challenging task. Part of the challenges comes from the intricacies and rich features of query languages, which makes reasoning about rewrite rules difficult. In this paper, we propose a machine-checkable denotational semantics for SQL, the de facto language for relational database, for rigorously validating rewrite rules. Unlike previously proposed semantics that are either non-mechanized or only cover a small amount of SQL language features, our semantics covers all major features of SQL, including bags, correlated subqueries, aggregation, and indexes. Our mechanized semantics, called HoTT SQL, is based on K-Relations and homotopy type theory, where we denote relations as mathematical functions from tuples to univalent types. We have implemented HoTTSQL in Coq, which takes only fewer than 300 lines of code and have proved a wide range of SQL rewrite rules, including those from database research literature (e.g., magic set rewrites) and real-world query optimizers (e.g., subquery elimination). Several of these rewrite rules have never been previously proven correct. In addition, while query equivalence is generally undecidable, we have implemented an automated decision procedure using HoTTSQL for conjunctive queries: a well studied decidable fragment of SQL that encompasses many real-world queries.

Ncode: an Open Source Bilingual N-gram SMT Toolkit

Abstract: This paper describes N, an open source statistical machine translation (SMT) toolkit for translation models estimated as n-gram language models of bilingual units (tuples). This toolkit includes tools for extracting tuples, estimating models and performing translation. It can be easily coupled to several other open source toolkits to yield a complete SMT pipeline. In this article, we review the main features of the toolkit and explain how to build a translation engine with N. We also report a short comparison with the widely known M system. Results show that N outperforms M in terms of memory requirements and translation speed. N also achieves slightly higher accuracy results.