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20152024
most citedIntroduction to Neural Network based Approaches for Question Answering over Knowledge Graphs

42 citations · 121 across the 24 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.CL2019

Using a KG-Copy Network for Non-Goal Oriented Dialogues

Debanjan Chaudhuri, Md Rashad Al Hasan Rony, Simon Jordan +1

Non-goal oriented, generative dialogue systems lack the ability to generate answers with grounded facts. A knowledge graph can be considered an abstraction of the real world consis…

cs.DB2019★ 16 cited

The Query Translation Landscape: a Survey

Mohamed Nadjib Mami, Damien Graux, Harsh Thakkar +3

Whereas the availability of data has seen a manyfold increase in past years, its value can be only shown if the data variety is effectively tackled ---one of the prominent Big Data…

cs.AI2019

Method for the semantic indexing of concept hierarchies, uniform representation, use of relational database systems and generic and case-based reasoning

Uwe Petersohn, Sandra Zimmer, Jens Lehmann

This paper presents a method for semantic indexing and describes its application in the field of knowledge representation. Starting point of the semantic indexing is the knowledge…

cs.CL2019★ 42 cited

Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs

Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari +3

Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an ov…

cs.CL2019★ 4 cited

Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function

Mojtaba Nayyeri, Xiaotian Zhou, Sahar Vahdati +2

Translation-based embedding models have gained significant attention in link prediction tasks for knowledge graphs. TransE is the primary model among translation-based embeddings a…

cs.AI2019★ 9 cited

Soft Marginal TransE for Scholarly Knowledge Graph Completion

Mojtaba Nayyeri, Sahar Vahdati, Jens Lehmann +1

Knowledge graphs (KGs), i.e. representation of information as a semantic graph, provide a significant test bed for many tasks including question answering, recommendation, and link…