TY - GEN
T1 - AMETHYST
T2 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
AU - Danilevsky, Marina
AU - Wang, Chi
AU - Tao, Fangbo
AU - Nguyen, Son
AU - Chen, Gong
AU - Desai, Nihit
AU - Wang, Lidan
AU - Han, Jiawei
N1 - Funding Information:
6. ACKNOWLEDGMENTS This work was supported in part by the U.S. National Science Foundation grants IIS–0905215, CNS-0931975, and IIS-1017362; U.S. Army Research Laboratory under Cooperative Agreement No. W911NF-09-2-0053 (NS-CTA); and IIS-1017362, U.S. Air Force Office of Scientific Research MURI award FA9550-08-1-0265, and MIAS, a DHS-IDS Center for Multimodal Information Access and Synthesis at UIUC. Chi Wang was supported by a Microsoft Research PhD Fellowship. Marina Danilevsky was supported by a National Science Foundation Graduate Research Fellowship grant NSF DGE 07-15088.
Funding Information:
This work was supported in part by the U.S. National Science Foundation grants IIS-0905215, CNS-0931975, and IIS- 1017362; U.S. Army Research Laboratory under Coopera-Tive Agreement No. W911NF-09-2-0053 (NS-CTA); and IIS- 1017362, U.S. Air Force Office of Scientific Research MURI award FA9550-08-1-0265, and MIAS, a DHS-IDS Center for Multimodal Information Access and Synthesis at UIUC. Chi Wang was supported by a Microsoft Research PhD Fellow- ship. Marina Danilevsky was supported by a National Sci- ence Foundation Graduate Research Fellowship grant NSF DGE 07-15088.
Publisher Copyright:
Copyright © 2013 ACM.
PY - 2013/8/11
Y1 - 2013/8/11
N2 - In this demo we present AMETHYST, a system for explor- ing and analyzing a topical hierarchy constructed from a heterogeneous information network (HIN). HINs, composed of multiple types of entities and links are very common in the real world. Many have a text component, and thus can benefit from a high quality hierarchical organization of the topics in the network dataset. By organizing the topics into a hierarchy, AMETHYST helps understand search results in the context of an ontology, and explain entity relatedness at different granularities. The automatically constructed top- ical hierarchy reflects a domain-specific ontology, interacts with multiple types of linked entities, and can be tailored for both free text and OLAP queries.
AB - In this demo we present AMETHYST, a system for explor- ing and analyzing a topical hierarchy constructed from a heterogeneous information network (HIN). HINs, composed of multiple types of entities and links are very common in the real world. Many have a text component, and thus can benefit from a high quality hierarchical organization of the topics in the network dataset. By organizing the topics into a hierarchy, AMETHYST helps understand search results in the context of an ontology, and explain entity relatedness at different granularities. The automatically constructed top- ical hierarchy reflects a domain-specific ontology, interacts with multiple types of linked entities, and can be tailored for both free text and OLAP queries.
KW - Entity mining
KW - Heterogeneous network
KW - Network analysis
KW - Topic modeling
UR - http://www.scopus.com/inward/record.url?scp=84938107404&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84938107404&partnerID=8YFLogxK
U2 - 10.1145/2487575.2487716
DO - 10.1145/2487575.2487716
M3 - Conference contribution
AN - SCOPUS:84938107404
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 1458
EP - 1461
BT - KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
A2 - Parekh, Rajesh
A2 - He, Jingrui
A2 - Inderjit, Dhillon S.
A2 - Bradley, Paul
A2 - Koren, Yehuda
A2 - Ghani, Rayid
A2 - Senator, Ted E.
A2 - Grossman, Robert L.
A2 - Uthurusamy, Ramasamy
PB - Association for Computing Machinery
Y2 - 11 August 2013 through 14 August 2013
ER -