Identifying animals with dynamic location-aware and semantic hierarchy-based image browsing for different cognitive style learners

Dunwei Wen, Ming Chi Liu, Yueh Min Huang, Kinshuk, Pi Hsia Hung

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

Abstract

Lack of overall ecological knowledge structure is a critical reason for learners' failure in keyword-based search. To address this issue, this paper firstly presents the dynamic location-aware and semantic hierarchy (DLASH) designed for the learners to browse images, which aims to identify learners' current interesting sights and provide adaptive assistance accordingly in ecological learning. The main idea is based on the observation that the species of plants and animals are discontinuously distributed around the planet, and hence their semantic hierarchy, besides its structural similarity with WordNet, is related to location information. This study then investigates how different cognitive styles of the learners influence the use of DLASH in their image browsing. The preliminary results show that the learners perform better when using DLASH based image browsing than using the Flickr one. In addition, cognitive styles have more effects on image browsing in the DLASH version than in the Flickr one.

Original languageEnglish
Title of host publicationProceedings - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010
Pages355-359
Number of pages5
DOIs
Publication statusPublished - 2010
Event10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010 - Sousse, Tunisia
Duration: 5 Jul. 20107 Jul. 2010

Publication series

NameProceedings - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010

Conference

Conference10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010
Country/TerritoryTunisia
CitySousse
Period5/07/107/07/10

Keywords

  • Congnitive styles
  • Ecological learning
  • Image browsing
  • Location-aware
  • Semantic analysis
  • Wikipedia
  • WordNet

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