A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf
.
Combining Citation Network Information and Text Similarity for Research Article Recommender Systems
2021
IEEE Access
Researchers often need to gather a comprehensive set of papers relevant to a focused topic, but this is often difficult and time-consuming using existing search methods. For example, keyword searching suffers from difficulties with synonyms and multiple meanings. While some automated research-paper recommender systems exist, these typically depend on either a researcher's entire library or just a single paper, resulting in either a quite broad or a quite narrow search. With these issues in
doi:10.1109/access.2021.3137960
fatcat:pudylweshvbrbgivyh4uumv46i