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Found 13 papers, 2 papers with code
KIQA: Knowledge-Infused Question Answering Model for Financial Table-Text Data
While entity retrieval models continue to advance their capabilities, our understanding of their wide-ranging applications is limited, especially in domain-specific settings.
iLab at FinCausal 2022: Enhancing Causality Detection with an External Cause-Effect Knowledge Graph
The application of span detection grows fast along with the increasing need of understanding the causes and effects of events, especially in the finance domain.
Negative Sampling in Knowledge Graph Representation Learning: A Review
This comprehensive survey paper systematically reviews various negative sampling (NS) methods and their contributions to the success of KGRL.
TuckerDNCaching: high-quality negative sampling with tucker decomposition
Knowledge Graph Embedding (KGE) translates entities and relations of knowledge graphs (KGs) into a low-dimensional vector space, enabling an efficient way of predicting missing facts.
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TabEAno: Table to Knowledge Graph Entity Annotation
In the Open Data era, a large number of table resources have been made available on the Web and data portals.
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
This paper presents the design of our system, namely MTab, for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019).
Combination of Unified Embedding Model and Observed Features for Knowledge Graph Completion
Then, we show that these models utilize paths for link prediction and propose a method for evaluating rules based on this idea.
Graph Pattern Entity Ranking Model for Knowledge Graph Completion
To solve this problem, many knowledge graph embedding models have been developed to populate knowledge graphs and these have shown outstanding performance.
EmbNum: Semantic labeling for numerical values with deep metric learning
Semantic labeling for numerical values is a task of assigning semantic labels to unknown numerical attributes.
Deep Reinforcement Learning Boosted by External Knowledge
Recent improvements in deep reinforcement learning have allowed to solve problems in many 2D domains such as Atari games.
TorusE: Knowledge Graph Embedding on a Lie Group
To the best of our knowledge, TorusE is the first model that embeds objects on other than a real or complex vector space, and this paper is the first to formally discuss the problem of regularization of TransE.
Integrating Know-How into the Linked Data Cloud
We describe a framework for representing generic know-how as Linked Data and for automatically acquiring this representation from existing resources on the Web.
Sub-Classifier Construction for Error Correcting Output Code Using Minimum Weight Perfect Matching
We propose a method for constructing the Error Correcting Output Code to obtain the suitable combination of positive and negative classes encoded to represent binary classifiers.
