(Apologies for multiple postings)

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**Call for Papers - Special Issue "Knowledge Graphs for Search and Recommendation" on Information (MDPI)**

https://www.mdpi.com/journal/information/special_issues/knowledge_graphs_for_search_and_recommendation

Guest Editors:

- Dr. Pierpaolo Basile (University of Bari, Italy)
- Dr. Annalina Caputo (Dublin City University, Ireland)

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Abstract:

The availability of large publicly available knowledge graph resources, such as Freebase, DBpedia, Wikidata, Yago, and Babelnet, has fostered new research directions, tasks, and application, in search and recommendation systems. Knowledge graphs are at the forefront of applications that try to bridge the semantic gap between structured and unstructured information in order to open new possibilities to represent, visualize, query, interact, and in general, make sense of information.

More recently, search and recommendation systems have benefited from developments in deep learning and graph embeddings, which have inspired new approaches to semantic matching, feature extraction, cold-start and long-tail problems, algorithm transparency and interpretability, entity, facet, and exploratory search.

This Special Issue welcomes submissions that provide new perspectives, introduce new challenges and tasks, as well as overview articles on the use of knowledge graphs in information retrieval and recommendation systems.

For more details, please visit the special issue website: https://www.mdpi.com/journal/information/special_issues/knowledge_graphs_for_search_and_recommendation


Topics:

- Knowledge graph representation and acquisition for search and recommendation
- Knowledge graph embeddings for search and recommendation
- Entity linking for search and recommendation
- Knowledge graph-based query expansion
- Knowledge graph-based information extraction
- Question answering over knowledge graphs
- Facet and exploratory search through knowledge graphs
- Result diversification through knowledge graphs
- Conversational systems based on knowledge graphs
- Knowledge graphs for recommendation explanation and transparency
- Entity and expert retrieval
- Application of knowledge graphs to retrieval and recommendation on specific domains: cultural heritage and digital humanities, medical, legal, etc.

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Submission:

Deadline for manuscript submissions: **28 February 2021**.

Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website.


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Annalina Caputo
Assistant Professor | School of Computing | Dublin City University
Academic Lead for MSc in Artificial Intelligence for ICT Skillnet
Funded Investigator, SFI I-FORM Centre
Academic Collaborator, SFI ADAPT Centre
annalina.caputo@dcu.ie | + 353 1 700 8056
Zoom: https://dcu-ie.zoom.us/my/annalina.caputo

School of Computing | Room L2.48 | McNulty Building | Dublin City University | Glasnevin | Dublin 9


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