PageRank evaluates the importance of Web pages with link relations. However, there is no direct method of evaluating the meaning of links in a hyperlink-based Web structure. This feature may cause problems in that pages containing many in-links are highly ranked without considering the meaning of the link relations among the pages. We therefore propose a novel ranking approach to directly analyze the
meaning of links by transforming a hyperlink-based Web structure into a semantic-link-based Web structure. We extract semantic metadata from Web pages and construct a semantic-link-based Web structure using RDF model. We define a metric to evaluate the weight of the links for stratifying rank values based on their importance in the semantic-link-based Web structure. We implement the weighted
semantic ranking algorithm in the MapReduce framework to consider large-scale semantic metadata. The results of our experiment show that our approach outperforms existing PageRank algorithms.
%0 Journal Article
%1 heegookjun2016metadatabased
%A Hee-Gook Jun, Dong-Hyuk Im Kim, Hyoung-Joo
%D 2016
%E Hao-En Chueh, Yuanpei University, Taiwan
%J International Journal of Web & Semantic Technology (IJWesT)
%K Big Data, MapReduce PageRank, RDF, Semantic Web,
%N 2
%P 11-24
%T An RDF Metadata-Based Weighted Semantic Pagerank Algorithm
%U http://airccse.org/journal/ijwest/current.html
%V 7
%X PageRank evaluates the importance of Web pages with link relations. However, there is no direct method of evaluating the meaning of links in a hyperlink-based Web structure. This feature may cause problems in that pages containing many in-links are highly ranked without considering the meaning of the link relations among the pages. We therefore propose a novel ranking approach to directly analyze the
meaning of links by transforming a hyperlink-based Web structure into a semantic-link-based Web structure. We extract semantic metadata from Web pages and construct a semantic-link-based Web structure using RDF model. We define a metric to evaluate the weight of the links for stratifying rank values based on their importance in the semantic-link-based Web structure. We implement the weighted
semantic ranking algorithm in the MapReduce framework to consider large-scale semantic metadata. The results of our experiment show that our approach outperforms existing PageRank algorithms.
@article{heegookjun2016metadatabased,
abstract = {PageRank evaluates the importance of Web pages with link relations. However, there is no direct method of evaluating the meaning of links in a hyperlink-based Web structure. This feature may cause problems in that pages containing many in-links are highly ranked without considering the meaning of the link relations among the pages. We therefore propose a novel ranking approach to directly analyze the
meaning of links by transforming a hyperlink-based Web structure into a semantic-link-based Web structure. We extract semantic metadata from Web pages and construct a semantic-link-based Web structure using RDF model. We define a metric to evaluate the weight of the links for stratifying rank values based on their importance in the semantic-link-based Web structure. We implement the weighted
semantic ranking algorithm in the MapReduce framework to consider large-scale semantic metadata. The results of our experiment show that our approach outperforms existing PageRank algorithms. },
added-at = {2017-01-05T01:04:04.000+0100},
author = {{Hee-Gook Jun, Dong-Hyuk Im Kim}, Hyoung-Joo},
biburl = {https://www.bibsonomy.org/bibtex/2dd908fe20747f6f7fb9289fd9b973f17/laimbee},
editor = {{Hao-En Chueh, Yuanpei University}, Taiwan},
interhash = {b42c633f796b428960ba3eba27d219d7},
intrahash = {dd908fe20747f6f7fb9289fd9b973f17},
journal = {International Journal of Web & Semantic Technology (IJWesT)},
keywords = {Big Data, MapReduce PageRank, RDF, Semantic Web,},
month = {April},
number = 2,
pages = {11-24},
timestamp = {2017-01-05T01:06:15.000+0100},
title = {An RDF Metadata-Based Weighted Semantic Pagerank Algorithm },
url = {http://airccse.org/journal/ijwest/current.html},
volume = 7,
year = 2016
}