2 citations · 4 across the 6 of their papers we have counts for
6 papers
CleanGraph: Human-in-the-loop Knowledge Graph Refinement and Completion
Tyler Bikaun, Michael Stewart, Wei Liu
This paper presents CleanGraph, an interactive web-based tool designed to facilitate the refinement and completion of knowledge graphs. Maintaining the reliability of knowledge gra…
Rel2Graph: Automated Mapping From Relational Databases to a Unified Property Knowledge Graph
Ziyu Zhao, Wei Liu, Tim French +1
Although a few approaches are proposed to convert relational databases to graphs, there is a genuine lack of systematic evaluation across a wider spectrum of databases. Recognising…
E2EET: From Pipeline to End-to-end Entity Typing via Transformer-Based Embeddings
Michael Stewart, Wei Liu
Entity Typing (ET) is the process of identifying the semantic types of every entity within a corpus. In contrast to Named Entity Recognition, where each token in a sentence is labe…
Word-level Lexical Normalisation using Context-Dependent Embeddings
Michael Stewart, Wei Liu, Rachel Cardell-Oliver
Lexical normalisation (LN) is the process of correcting each word in a dataset to its canonical form so that it may be more easily and more accurately analysed. Most lexical normal…
ICDM 2019 Knowledge Graph Contest: Team UWA
Michael Stewart, Majigsuren Enkhsaikhan, Wei Liu
We present an overview of our triple extraction system for the ICDM 2019 Knowledge Graph Contest. Our system uses a pipeline-based approach to extract a set of triples from a given…
Natural Language Feature Selection via Cooccurrence
Cory O. Root
Specificity is important for extracting collocations, keyphrases, multi-word and index terms [Newman et al. 2012]. It is also useful for tagging, ontology construction [Ryu and Cho…