TY - GEN
T1 - Interlinking documents based on semantic graphs with an application
AU - Nunes, Bernardo Pereira
AU - Fetahu, Besnik
AU - Kawase, Ricardo
AU - Dietze, Stefan
AU - Casanova, Marco Antonio
AU - Maynard, Diana
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Connectivity and relatedness of Web resources are two concepts that define to what extent different parts are connected or related to one another. Measuring connectivity and relatedness between Web resources is a growing field of research, often the starting point of recommender systems. Although relatedness is liable to subjective interpretations, connectivity is not. Given the Semantic Web’s ability of linking Web resources, connectivity can be measured by exploiting the links between entities. Further, these connections can be exploited to uncover relationships between Web resources. This chapter describes the application and expansion of a relationship assessment methodology from social network theory to measure the connectivity between documents. The connectivity measures are used to identify connected and related Web resources. The approach is able to expose relations that traditional text-based approaches fail to identify. The proposed approaches are validated and assessed through an evaluation on a real-world dataset, where results show that the proposed techniques outperform state of the art approaches. Finally, a Web-based application called Cite4Me that uses the proposed approach is presented.
AB - Connectivity and relatedness of Web resources are two concepts that define to what extent different parts are connected or related to one another. Measuring connectivity and relatedness between Web resources is a growing field of research, often the starting point of recommender systems. Although relatedness is liable to subjective interpretations, connectivity is not. Given the Semantic Web’s ability of linking Web resources, connectivity can be measured by exploiting the links between entities. Further, these connections can be exploited to uncover relationships between Web resources. This chapter describes the application and expansion of a relationship assessment methodology from social network theory to measure the connectivity between documents. The connectivity measures are used to identify connected and related Web resources. The approach is able to expose relations that traditional text-based approaches fail to identify. The proposed approaches are validated and assessed through an evaluation on a real-world dataset, where results show that the proposed techniques outperform state of the art approaches. Finally, a Web-based application called Cite4Me that uses the proposed approach is presented.
KW - Document Connectivity
KW - Semantic Connections
KW - Semantic Graphs
UR - http://www.scopus.com/inward/record.url?scp=84922015397&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-13545-8_9
DO - 10.1007/978-3-319-13545-8_9
M3 - Conference contribution
T3 - Smart Innovation, Systems and Technologies
SP - 139
EP - 155
BT - SOFSEM 2015
A2 - Tweedale, Jeffrey W.
A2 - Jain, Lakhmi C.
A2 - Jain, Lakhmi C.
A2 - Tweedale, Jeffrey W.
A2 - Watada, Junzo
A2 - Howlett, Robert J.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 17th Annual Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2013
Y2 - 9 September 2013 through 11 September 2013
ER -