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

Mehdi Terdjimi 1, 2 Lionel Médini 1 Michael Mrissa 2
1 TWEAK - Traces, Web, Education, Adaptation, Knowledge
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 SOC - Service Oriented Computing
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
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.
Complete list of metadatas

Cited literature [8 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01276558
Contributor : Mehdi Terdjimi <>
Submitted on : Friday, February 19, 2016 - 3:50:19 PM
Last modification on : Friday, April 26, 2019 - 11:16:01 PM

File

Demo_www2016.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01276558, version 1

Citation

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⟩

Share

Metrics

Record views

324

Files downloads

152