Leveraging Trust Relations to Improve Academic Patent Recommendation

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dc.contributor.authorChen, Yuwen
dc.contributor.authorMa, Jian
dc.contributor.authorZhu, Peihu
dc.contributor.authorHuang, Xiaoming
dc.contributor.authorJin, Qin
dc.date.accessioned2021-12-24T17:29:06Z
dc.date.available2021-12-24T17:29:06Z
dc.date.issued2022-01-04
dc.description.abstractAcademic patent trading is one of the important ways for university technology transfer. Compared to industry patent trading, academic patent trading suffers from a more serious information asymmetric problem. It needs a recommendation service to help companies identify academic patents that they want to pay. However, existing recommendation approaches have limitations in facilitating academic patent trading in online patent platforms because most of them only consider patent-level characteristics. A high trust degree of a company towards academic patents can alleviate the information asymmetry and encourage trading. This study proposes a novel academic patent recommendation approach with a hybrid strategy, combining citation-based relevance, connectivity, and trustworthiness. An offline experiment is conducted to evaluate the performance of the proposed recommendation approach. The results show that the proposed method performs better than the baseline methods in both accuracy and ranking.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2022.171
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79503
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision Support for Smart City
dc.subjecthybrid recommendation
dc.subjectpatent recommendation
dc.subjectpatent trading
dc.subjecttrust
dc.subjectuniversity technology transfer
dc.titleLeveraging Trust Relations to Improve Academic Patent Recommendation
dc.type.dcmitext

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