Is comprehension useful for mobile semantic search engines?

Authors:
Ahmad Ali Iqbal;Aruna Seneviratne
Affiliations:
School of EE&T, University of New South Wales, Australia;National Information and Communication Technology Australia
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Year:
2010

Citing 8
Cited 0

Summary cache: a scalable wide-area web cache sharing protocol

IEEE/ACM Transactions on Networking (TON)
Sentence reduction for automatic text summarization

ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Implementation and Evaluation of a Distributed RDF Storage and Retrieval System

WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
Ontology summarization based on rdf sentence graph

Proceedings of the 16th international conference on World Wide Web
AquaLog: An ontology-driven question answering system for organizational semantic intranets

Web Semantics: Science, Services and Agents on the World Wide Web
An Empirical Evaluation on Semantic Search Performance of Keyword-Based and Semantic Search Engines: Google, Yahoo, Msn and Hakia

ICIMP '09 Proceedings of the 2009 Fourth International Conference on Internet Monitoring and Protection
Boosting semantic web data access using Swoogle

AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
Removing the redundancy from distributed semantic web data

DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Semantic web is gaining popularity as a candidate for next generation World Wide Web. In recent years, there has been a tremendous increase of using Internet on mobile devices and search engines are considered essential for Internet users. The existing search engines have been designed for powerful computers and are highly resource hungry, while mobiles have limited computational resources. In this paper, we study the use of comprehension for aiding the search engine results for mobile users. Our preliminary evaluation shows the promising results for comprehension generation.