Sideway Value Algebra for Object-Relational Databases

Abstract

Using functions in various forms, recent database publications have assigned "scores", "preference values", and "probabilistic values" to object-relational database tuples. We generalize these functions and their evaluations as sideway functions and sideway values, respectively. Sideway values represent the advices (recommendations) of data creators or preferences of users, and are employed for the purposes of ranking query outputs and limiting output sizes during query evaluation as well as for application-dependent querying.This paper introduces SQL extensions and a sideway value algebra (SVA) for object-relational databases. SVA operators modify and propagate sideway values of base relations in automated and generic ways. We define the SVA join, and a recursive SVA closure operator, called TClosure. Output tuples of the SVA join operator are assigned sideway values on the basis of the sideway values and similarities of joined tuples, and the operator returns the highest ranking tuples. TClosure operator recursively expands a given set of objects (as tuples) according to a given regular expression of relationship types, and derives sideway values for the set of newly reached objects.We present evaluation algorithms for SVA join and TClosure operators, and report experimental results on the performance of the operators using the DBLP Bibliography data and synthetic data.

Querying structured text in an XML database

“…It requires the preference function to be "monotonic" and assumes that a ceiling value of the function can be easily derived. Sideway Value Algebra (SVA) [19], on the other hand, focuses on the algebraic representation of those preference scores without worrying about how they are generated. It keeps the preference scores as sideway values and propagate them during the evaluation of the algebraic operators.…”

Metadata‐based modeling of information resources on the Web

“…In this paper, we essentially describe the Web information space model with expert advice repositories at its heart, and focus on the properties of topic/metalink based model, as well as some practical issues for their automated creation. In Özsoyoǧlu et al (2002), we also describe SQL extensions for querying expert advice repositories for Web querying purposes, along with an algebra and query processing algorithms. While we propose a metadata‐based search and querying paradigm for specific subnets on the Web, the previously proposed Web query languages in the literature (see Florescu, Levy, & Mendelzon [ 1998] for an extensive survey) have the broader goal of querying the Web as a whole.…”

“…Then, user queries that require computing the closure of a topic with respect to a (set of) metalink(s) can be safely evaluated. In Özsoyoǧlu et al (2002), we specify topic closure computation algorithms for more general cases, i.e., regular expressions of metalink types.…”

“…Figure 8 presents papers with names similar to “Real time transaction in mobile databases,” where the user can see the prerequisites of the highlighted paper in the list by just clicking on the corresponding button. Note that such queries can be expressed in SQL with some extensions, which we discuss elsewhere along with the query processing algorithms (Özsoyoǧlu et al, 2002).…”

“…Note that, while we essentially focus on the Web information space model in this paper, we also study issues to use this model for Web querying purposes. In Özsoyoǧlu et al (2002), we define an algebra and query processing algorithms that extend SQL (Structural Query Language) for querying expert advice repositories with some specific operators.…”