Efficient Web Browsing with Semantic Annotation: A Case Study of Product Images in E-Commerce Sites

Jason J. JUNG; Kee-Sung LEE; Seung-Bo PARK; Geun-Sik JO

doi:10.1093/ietisy/e88-d.5.843

Efficient Web Browsing with Semantic Annotation: A Case Study of Product Images in E-Commerce Sites

Jason J. JUNG, Kee-Sung LEE, Seung-Bo PARK, Geun-Sik JO

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Web browsing task is based on depth-first searching scheme, so that searching relevant information from Web may be very tedious. In this paper, we propose personal browsing assistant system based on user intentions modeling. Before explicitly requested by a user, this system can analyze the prefetched resources from the hyperlinked Webpages and compare them with the estimated user intention, so that it can help him to make a better decision like which Webpage should be requested next. More important problem is the semantic heterogeneity between Web spaces. It makes the understandability of locally annotated resources more difficult. We apply semantic annotation, which is a transcoding procedure with the global ontology. Therefore, each local metadata can be semantically enriched, and efficiently comparable. As testing bed of our experiment, we organized three different online clothes stores whose images are annotated by semantically heterogeneous metadata. We simulated virtual customers navigating these cyberspaces. According to the predefined preferences of customer models, they conducted comparison-shopping. We have shown the reasonability of supporting the Web browsing, and its performance was evaluated as measuring the total size of browsed hyperspace.

Publication: IEICE TRANSACTIONS on Information Vol.E88-D No.5 pp.843-850

Publication Date: 2005/05/01

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DOI: 10.1093/ietisy/e88-d.5.843

Type of Manuscript: Special Section PAPER (Special Section on Cyberworlds)

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Jason J. JUNG, Kee-Sung LEE, Seung-Bo PARK, Geun-Sik JO, "Efficient Web Browsing with Semantic Annotation: A Case Study of Product Images in E-Commerce Sites" in IEICE TRANSACTIONS on Information, vol. E88-D, no. 5, pp. 843-850, May 2005, doi: 10.1093/ietisy/e88-d.5.843.
Abstract: Web browsing task is based on depth-first searching scheme, so that searching relevant information from Web may be very tedious. In this paper, we propose personal browsing assistant system based on user intentions modeling. Before explicitly requested by a user, this system can analyze the prefetched resources from the hyperlinked Webpages and compare them with the estimated user intention, so that it can help him to make a better decision like which Webpage should be requested next. More important problem is the semantic heterogeneity between Web spaces. It makes the understandability of locally annotated resources more difficult. We apply semantic annotation, which is a transcoding procedure with the global ontology. Therefore, each local metadata can be semantically enriched, and efficiently comparable. As testing bed of our experiment, we organized three different online clothes stores whose images are annotated by semantically heterogeneous metadata. We simulated virtual customers navigating these cyberspaces. According to the predefined preferences of customer models, they conducted comparison-shopping. We have shown the reasonability of supporting the Web browsing, and its performance was evaluated as measuring the total size of browsed hyperspace.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.5.843/_p

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@ARTICLE{e88-d_5_843,
author={Jason J. JUNG, Kee-Sung LEE, Seung-Bo PARK, Geun-Sik JO, },
journal={IEICE TRANSACTIONS on Information},
title={Efficient Web Browsing with Semantic Annotation: A Case Study of Product Images in E-Commerce Sites},
year={2005},
volume={E88-D},
number={5},
pages={843-850},
abstract={Web browsing task is based on depth-first searching scheme, so that searching relevant information from Web may be very tedious. In this paper, we propose personal browsing assistant system based on user intentions modeling. Before explicitly requested by a user, this system can analyze the prefetched resources from the hyperlinked Webpages and compare them with the estimated user intention, so that it can help him to make a better decision like which Webpage should be requested next. More important problem is the semantic heterogeneity between Web spaces. It makes the understandability of locally annotated resources more difficult. We apply semantic annotation, which is a transcoding procedure with the global ontology. Therefore, each local metadata can be semantically enriched, and efficiently comparable. As testing bed of our experiment, we organized three different online clothes stores whose images are annotated by semantically heterogeneous metadata. We simulated virtual customers navigating these cyberspaces. According to the predefined preferences of customer models, they conducted comparison-shopping. We have shown the reasonability of supporting the Web browsing, and its performance was evaluated as measuring the total size of browsed hyperspace.},
keywords={},
doi={10.1093/ietisy/e88-d.5.843},
ISSN={},
month={May},}

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TY - JOUR
TI - Efficient Web Browsing with Semantic Annotation: A Case Study of Product Images in E-Commerce Sites
T2 - IEICE TRANSACTIONS on Information
SP - 843
EP - 850
AU - Jason J. JUNG
AU - Kee-Sung LEE
AU - Seung-Bo PARK
AU - Geun-Sik JO
PY - 2005
DO - 10.1093/ietisy/e88-d.5.843
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2005
AB - Web browsing task is based on depth-first searching scheme, so that searching relevant information from Web may be very tedious. In this paper, we propose personal browsing assistant system based on user intentions modeling. Before explicitly requested by a user, this system can analyze the prefetched resources from the hyperlinked Webpages and compare them with the estimated user intention, so that it can help him to make a better decision like which Webpage should be requested next. More important problem is the semantic heterogeneity between Web spaces. It makes the understandability of locally annotated resources more difficult. We apply semantic annotation, which is a transcoding procedure with the global ontology. Therefore, each local metadata can be semantically enriched, and efficiently comparable. As testing bed of our experiment, we organized three different online clothes stores whose images are annotated by semantically heterogeneous metadata. We simulated virtual customers navigating these cyberspaces. According to the predefined preferences of customer models, they conducted comparison-shopping. We have shown the reasonability of supporting the Web browsing, and its performance was evaluated as measuring the total size of browsed hyperspace.
ER -