43 citations · 75 across the 17 of their papers we have counts for
18 papers
HopfE: Knowledge Graph Representation Learning using Inverse Hopf Fibrations
Anson Bastos, Kuldeep Singh, Abhishek Nadgeri +3
Recently, several Knowledge Graph Embedding (KGE) approaches have been devised to represent entities and relations in dense vector space and employed in downstream tasks such as li…
KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Abhishek Nadgeri, Anson Bastos, Kuldeep Singh +4
We present a novel method for relation extraction (RE) from a single sentence, mapping the sentence and two given entities to a canonical fact in a knowledge graph (KG). Especially…
Capturing Knowledge of Emerging Entities From Extended Search Snippets
Sunday C. Ngwobia, Saeedeh Shekarpour, Faisal Alshargi
Google and other search engines feature the entity search by representing a knowledge card summarizing related facts about the user-supplied entity. However, the knowledge card is…
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata
Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang' +3
In this paper, we propose CHOLAN, a modular approach to target end-to-end entity linking (EL) over knowledge bases. CHOLAN consists of a pipeline of two transformer-based models in…
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh +4
In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG). R…
Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking
Isaiah Onando Mulang, Kuldeep Singh, Akhilesh Vyas +4
The collaborative knowledge graphs such as Wikidata excessively rely on the crowd to author the information. Since the crowd is not bound to a standard protocol for assigning entit…
Towards Optimisation of Collaborative Question Answering over Knowledge Graphs
Kuldeep Singh, Mohamad Yaser Jaradeh, Saeedeh Shekarpour +5
Collaborative Question Answering (CQA) frameworks for knowledge graphs aim at integrating existing question answering (QA) components for implementing sequences of QA tasks (i.e. Q…
HCqa: Hybrid and Complex Question Answering on Textual Corpus and Knowledge Graph
Somayeh Asadifar, Mohsen Kahani, Saeedeh Shekarpour
Question Answering (QA) systems provide easy access to the vast amount of knowledge without having to know the underlying complex structure of the knowledge. The research community…
Analyzing and learning the language for different types of harassment
Mohammadreza Rezvan, Saeedeh Shekarpour, Faisal Alshargi +3
Disclaimer: This paper is concerned with violent online harassment. To describe the subject at an adequate level of realism, examples of our collected tweets involve violent, threa…
empathi: An ontology for Emergency Managing and Planning about Hazard Crisis
Manas Gaur, Saeedeh Shekarpour, Amelie Gyrard +1
In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from…
No One is Perfect: Analysing the Performance of Question Answering Components over the DBpedia Knowledge Graph
Kuldeep Singh, Ioanna Lytra, Arun Sethupat Radhakrishna +3
Question answering (QA) over knowledge graphs has gained significant momentum over the past five years due to the increasing availability of large knowledge graphs and the rising i…
Principles for Developing a Knowledge Graph of Interlinked Events from News Headlines on Twitter
Saeedeh Shekarpour, Ankita Saxena, Krishnaprasad Thirunarayan +2
The ever-growing datasets published on Linked Open Data mainly contain encyclopedic information. However, there is a lack of quality structured and semantically annotated datasets…
Concept2vec: Metrics for Evaluating Quality of Embeddings for Ontological Concepts
Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru +1
Although there is an emerging trend towards generating embeddings for primarily unstructured data and, recently, for structured data, no systematic suite for measuring the quality…
A Quality Type-aware Annotated Corpus and Lexicon for Harassment Research
Mohammadreza Rezvan, Saeedeh Shekarpour, Lakshika Balasuriya +3
Having a quality annotated corpus is essential especially for applied research. Despite the recent focus of Web science community on researching about cyberbullying, the community…
CEVO: Comprehensive EVent Ontology Enhancing Cognitive Annotation
Saeedeh Shekarpour, Faisal Alshargi, Valerie Shalin +2
While the general analysis of named entities has received substantial research attention on unstructured as well as structured data, the analysis of relations among named entities…
Question Answering on Linked Data: Challenges and Future Directions
Saeedeh Shekarpour, Denis Lukovnikov, Ashwini Jaya Kumar +4
Question Answering (QA) systems are becoming the inspiring model for the future of search engines. While recently, underlying datasets for QA systems have been promoted from unstru…
Co-evolution of RDF Datasets
Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour +1
Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastru…
The WDAqua ITN: Answering Questions using Web Data
Christoph Lange, Saeedeh Shekarpour, Soren Auer
WDAqua is a Marie Curie Innovative Training Network (ITN) and is funded under EU grant number 642795 and runs from January 2015 to December 2018. WDAqua aims at advancing the state…