![]() ![]() Authors may use MDPI'sĮnglish editing service prior to publication or during author revisions. Submitted papers should be well formatted and use good English. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Please visit the Instructions for Authors page before submitting a manuscript. ![]() Information is an international peer-reviewed open access monthly journal published by MDPI. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. All manuscripts are thoroughly refereed through a single-blind peer-review process. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website. Research articles, review articles as well as short communications are invited. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. All submissions that pass pre-check are peer-reviewed. Manuscripts can be submitted until the deadline. ![]() Once you are registered, click here to go to the submission form. Manuscripts should be submitted online at by registering and logging in to this website. 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. 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. 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. 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. The MDPI Information journal invites submissions to a Special Issue on “Knowledge Graphs for Search and Recommendation”. ![]()
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