Common knowledge and only knowing capture two intuitive and natural notions that have proven to be useful in a variety of settings, for example to reason about coordination or agreement between agents, or to analyse the knowledge of knowledge-based a...
Repository for "Turkish Wikipedia Based Knowledge Graph (Vikipedi Tabanlı Türkçe Bilgi Çizgesi)" of inzva AI Projects #6 (⭐ 28)
services, and software. Knowledge-based configuration is a major application area for artificial intelligence (AI), and it is based on modelling of the configurations
Aug 8, 2025 · Knowledge-based systems (KBS) are an application of artificial intelligence (AI) that rely on an information store and reasoning logic to provide answers. Knowledge-based systems are often …
Knowledge-based authentication, commonly referred to as KBA, is a method of authentication which seeks to prove the identity of someone accessing a service
Translation-based knowledge graph embedding has been one of the most important branches for knowledge representation learning since TransE came out. Although many translation-based approaches have achieved some progress in recent years, the performan...
Real-world semantic or knowledge-based systems, e.g., in the biomedical domain, can become large and complex. Tool support for the localization and repair of faults within knowledge bases of such systems can therefore be essential for their practical...
Mar 10, 2025 · Knowledge-Based Systems (KBSes) are AI tools that use extensive knowledge bases to assist in problem-solving and decision-making processes across various domains.
Jan 27, 2025 · Knowledge-based systems are a form of artificial intelligence (AI) designed to capture the knowledge of human experts to support decision-making. An expert system is an example of a …
Knowledge tracing (KT) aims to assess individuals' evolving knowledge states according to their learning interactions with different exercises in online learning systems (OIS), which is critical in supporting decision-making for subsequent intelligen...
The dynamic nature of real-world information necessitates efficient knowledge editing (KE) in large language models (LLMs) for knowledge updating. However, current KE approaches, which typically operate on (subject, relation, object) triples, ignore...
This paper describes Luminoso's participation in SemEval 2017 Task 2, "Multilingual and Cross-lingual Semantic Word Similarity", with a system based on ConceptNet. ConceptNet is an open, multilingual knowledge graph that focuses on general knowledge...
Knowledge bases, and their representations in the form of knowledge graphs (KGs), are naturally incomplete. Since scientific and industrial applications have extensively adopted them, there is a high demand for solutions that complete their informati...
This paper elaborates on the Triple Helix model for measuring the emergence of a knowledge base of socio-economic systems. The 'knowledge infrastructure' is measured using multiple indicators: webometric, scientometric, and technometric. The paper...
The contributions of model complexity, data volume, and feature modalities to knowledge graph-based drug repurposing remain poorly quantified under rigorous temporal validation. We constructed a pharmacology knowledge graph from ChEMBL 36 comprising...
Knowledge Graphs (KGs) have been used to support a wide range of applications, from web search to personal assistant. In this paper, we describe three generations of knowledge graphs: entity-based KGs, which have been supporting general search and qu...
Luminoso participated in the SemEval 2018 task on "Capturing Discriminative Attributes" with a system based on ConceptNet, an open knowledge graph focused on general knowledge. In this paper, we describe how we trained a linear classifier on a small...
Search systems are increasingly used for gaining knowledge through accessing relevant resources from a vast volume of content. However, search systems provide only limited support to users in knowledge acquisition contexts. Specifically, they do not...
We present an effective graph neural network (GNN)-based knowledge graph embedding model, which we name WGE, to capture entity- and relation-focused graph structures. Given a knowledge graph, WGE builds a single undirected entity-focused graph that v...
knowledge-based products and services. However, as discussed by Stewart (1996) knowledge is very different from physical products. For example, it can