Paper Info
Title
EgoSet: Exploiting Word Ego-networks and User-generated Ontology for Multifaceted Set Expansion.
Abstract
A key challenge of entity set expansion is that multifaceted input seeds can lead to significant incoherence in the result set. In this paper, we present a novel solution to handling multifaceted seeds by combining existing user-generated ontologies with a novel word-similarity metric based on skip-grams. By blending the two resources we are able to produce sparse word ego-networks that are centered on the seed terms and are able to capture semantic equivalence among words. We demonstrate that the resulting networks possess internally-coherent clusters, which can be exploited to provide non-overlapping expansions, in order to reflect different semantic classes of the seeds. Empirical evaluation against state-of-the-art baselines shows that our solution, EgoSet, is able to not only capture multiple facets in the input query, but also generate expansions for each facet with higher precision.
Year
DOI
Venue
2016
10.1145/2835776.2835808
WSDM
Field
DocType
Citations 
Ontology (information science),Data mining,Ontology,Web mining,Result set,Information retrieval,Computer science,Id, ego and super-ego,Information extraction,Semantic equivalence,Set expansion
Conference
17
PageRank 
References 
Authors
0.62
28
4
Name
Order
Citations
PageRank
Xin Rong1332.63
Zhe Chen2833.28
Qiaozhu Mei34395207.09
Eytan Adar4506.34