Existing knowledge graph instance matching approaches rely on embeddings to represent data in the form of vectors. They aim to capture the semantic meaning of ...

In this work, we present VDLS, an approach for automatic alignment of instances in RDF knowledge base graphs. VDLS generates for each instance a virtual ...

We propose a random walk-based approach for instance matching in knowledge graphs. •. We build an expanded candidates association graph consisting of pairs ...

Our method composes an instance-based matcher that casts the schema matching process as a two-way text classification task by exploiting instances of KG classes ...

Experiment results on the constructed data collections and two real-world datasets indicate that MultiObJ and FTRLIM outperform other state-of-the-art methods.

Apr 27, 2020 · Instance matching (IM) is the process of matching instances across Knowledge Bases (KBs) that refer to the same real-world object (eg, ...

We survey and discuss the state‐of‐the‐art IM methods regarding the context information. We, furthermore, describe and compare different state‐of‐the‐art IM ...

Many methods have been proposed to complete the instance matching task. Several state-of-the-art instance matching methods evolve from ontology matching methods ...

Abstract—Entity alignment (EA) finds equivalent entities that are located in different knowledge graphs (KGs), which is an essential.

This work focuses on instance matching – one of the subtasks of automatically populating the knowledge graph with data from a wide spectrum of external sources.