Home News About Us Contact Contributors Disclaimer Privacy Policy Help FAQ

Home
Search
Quick Search
Advanced
Fulltext
Browse
Collections
Persons
My eDoc
Session History
Login
Name:
Password:
Documentation
Help
Support Wiki
Direct access to
document ID:


          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 461779.0, MPI für biologische Kybernetik / Biologische Kybernetik
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction
Authors:Kashima, H.; Kato, T.; Yamanishi, Y.; Sugiyama, M.; Tsuda, K.
Editors:Park, H.; Parthasarathy, S.; Liu, H.
Date of Publication (YYYY-MM-DD):2009-05
Title of Proceedings:Proceedings of the 2009 SIAM International Conference on Data Mining (SDM 2009)
Start Page:1099
End Page:1110
Physical Description:12
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:We propose Link Propagation as a new semi-supervised learning
method for link prediction problems, where the task is to predict
unknown parts of the network structure by using auxiliary information
such as node similarities. Since the proposed method can
fill in missing parts of tensors, it is applicable to multi-relational
domains, allowing us to handle multiple types of links simultaneously.
We also give a novel efficient algorithm for Link Propagation
based on an accelerated conjugate gradient method.
External Publication Status:published
Document Type:Conference-Paper
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:LOCALID:5654
URL:http://www.siam.org/meetings/sdm09/
The scope and number of records on eDoc is subject to the collection policies defined by each institute - see "info" button in the collection browse view.