Bing-CSF-IDF+: A Semantics-Driven Recommender System for News-Reference-Cited by-同舟云学术

Bing-CSF-IDF+: A Semantics-Driven Recommender System for News

Published:2020 Issue: Volume: Page:143-153
ISSN:1865-0929
Container-title:Communications in Computer and Information Science
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Author:

van Huijsduijnen Lies Hooft,Hoogmoed Thom,Keulers Geertje,Langendoen Edmar,Langendoen Sanne,Vos Tim,Hogenboom Frederik,Frasincar Flavius^ORCID,Robal Tarmo^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-54623-6_13

Reference21 articles.

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2. Lecture Notes in Computer Science;E Brocken,2019

3. Burke, R.: Hybrid Recommender Systems: Survey and Experiments. User Model. User-Adap. Inter 12(4), 331–370 (2002). https://doi.org/10.1023/A:1021240730564

4. Capelle, M., Hogenboom, F., Hogenboom, A., Frasincar, F.: Semantic news recommendation using wordnet and bing similarities. In: 28th Symposium on Applied Computing (SAC 2013), The Semantic Web and its Application Track, pp. 296–302. ACM (2013)

5. Capelle, M., Moerland, M., Frasincar, F., Hogenboom, F.: Semantics-based news recommendation. In: 2nd International Conference on Web Intelligence, Mining and Semantics (WIMS 2012). ACM (2012)

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1. A survey on knowledge-aware news recommender systems;Semantic Web;2022-09-06

2. Enhancing Semantics-Driven Recommender Systems with Visual Features;Advanced Information Systems Engineering;2022

3. Addressing Scalability Issues in Semantics-Driven Recommender Systems;IEEE/WIC/ACM International Conference on Web Intelligence;2021-12-14