HyLAR+: Improving Hybrid Location-Agnostic Reasoning with Incremental Rule-based Update - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

HyLAR+: Improving Hybrid Location-Agnostic Reasoning with Incremental Rule-based Update

Abstract

Web applications that rely on datasets of limited sizes to handle small but frequent updates and numerous queries have no simple way to define where data should be stored and processed. We propose a reasoning framework that can be integrated in Web applications and is able to perform the same reasoning tasks on both client or server sides. This framework embeds a rule-based reasoning engine that uses an algorithm relying on both incremental reasoning and named graphs. We evaluate the performance of our approach and compare the effects of incremental reasoning and named graphs in different experimental conditions. Results show that our reasoner can significantly reduce response times to INSERT and DELETE queries. During the demo we will exhibit how it can be used to perform reasoning tasks based on client-generated information and improve Web applications with location-agnostic reasoning.
Fichier principal
Vignette du fichier
Demo_www2016.pdf (575.23 Ko) Télécharger le fichier
Origin Files produced by the author(s)
Loading...

Dates and versions

hal-01276558 , version 1 (19-02-2016)

Identifiers

  • HAL Id : hal-01276558 , version 1

Cite

Mehdi Terdjimi, Lionel Médini, Michael Mrissa. HyLAR+: Improving Hybrid Location-Agnostic Reasoning with Incremental Rule-based Update. WWW '16: 25th International World Wide Web Conference Companion, Apr 2016, Montréal, Canada. ⟨hal-01276558⟩
257 View
422 Download

Share

Gmail Mastodon Facebook X LinkedIn More