DeepAI AI Chat
Log In Sign Up

Link Analysis meets Ontologies: Are Embeddings the Answer?

by   Sebastian Mežnar, et al.

The increasing amounts of semantic resources offer valuable storage of human knowledge; however, the probability of wrong entries increases with the increased size. The development of approaches that identify potentially spurious parts of a given knowledge base is thus becoming an increasingly important area of interest. In this work, we present a systematic evaluation of whether structure-only link analysis methods can already offer a scalable means to detecting possible anomalies, as well as potentially interesting novel relation candidates. Evaluating thirteen methods on eight different semantic resources, including Gene Ontology, Food Ontology, Marine Ontology and similar, we demonstrated that structure-only link analysis could offer scalable anomaly detection for a subset of the data sets. Further, we demonstrated that by considering symbolic node embedding, explanations of the predictions (links) could be obtained, making this branch of methods potentially more valuable than the black-box only ones. To our knowledge, this is currently one of the most extensive systematic studies of the applicability of different types of link analysis methods across semantic resources from different domains.


page 12

page 14


Semantic Reasoning from Model-Agnostic Explanations

With the wide adoption of black-box models, instance-based post hoc expl...

Knowledge-Based Dataset for Training PE Malware Detection Models

Ontologies are a standard for semantic schemata in many knowledge-intens...

Test-Driven Development of ontologies (extended version)

Emerging ontology authoring methods to add knowledge to an ontology focu...

Semantic Answer Type and Relation Prediction Task (SMART 2021)

Each year the International Semantic Web Conference organizes a set of S...

Abstractive Tabular Dataset Summarization via Knowledge Base Semantic Embeddings

This paper describes an abstractive summarization method for tabular dat...

Multifaceted Context Representation using Dual Attention for Ontology Alignment

Ontology Alignment is an important research problem that finds applicati...