Martin, Germán Hurtado, Schockaert, Steven ![]() |
Official URL: http://link.springer.com/chapter/10.1007/978-3-642...
Abstract
While collaborative filtering and citation analysis have been well studied for research paper recommender systems, content-based approaches typically restrict themselves to straightforward application of the vector space model. However, various types of metadata containing potentially useful information are usually available as well. Our work explores several methods to exploit this information in combination with different similarity measures.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Publication |
Status: | Published |
Schools: | Computer Science & Informatics |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources |
Publisher: | Springer-Verlag |
ISBN: | 9783642154638 |
Last Modified: | 20 Oct 2022 09:24 |
URI: | https://orca.cardiff.ac.uk/id/eprint/31836 |
Citation Data
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