Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/93357
DC Field | Value | Language |
---|---|---|
dc.contributor | School of Accounting and Finance | en_US |
dc.creator | Yang, YC | en_US |
dc.creator | Ke, YS | en_US |
dc.creator | Wu, W | en_US |
dc.creator | Lin, KP | en_US |
dc.creator | Jin, Y | en_US |
dc.date.accessioned | 2022-06-21T08:22:07Z | - |
dc.date.available | 2022-06-21T08:22:07Z | - |
dc.identifier.issn | 0302-9743 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/93357 | - |
dc.description | 6th International Conference on HCI in Business, Government, and Organizations, HCIBGO 2019, held as part of the 21st International Conference on Human-Computer Interaction, HCI International 2019, Orlando, FL, USA, July 26-31, 2019 | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.rights | © Springer Nature Switzerland AG 2019. | en_US |
dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-030-22338-0_12 | en_US |
dc.subject | Financial kernel | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Mergers and acquisitions | en_US |
dc.subject | Recommendation service | en_US |
dc.subject | Support vector machine | en_US |
dc.title | Recommendation as a service in mergers and acquisitions transactions | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 151 | en_US |
dc.identifier.epage | 159 | en_US |
dc.identifier.volume | 11589 | en_US |
dc.identifier.doi | 10.1007/978-3-030-22338-0_12 | en_US |
dcterms.abstract | Mergers and acquisitions (M&A) happens frequently between corporations to combine and/or transfer their ownerships, operating units and assets. The purpose of the study is to develop a service that is able to recommend a feasible M&A deal. We integrate the support vector machine model with the kernel tricks to automatically determine M&A deals. In the end of the study, our proposed technique is empirically validated, and the results show the effectiveness of the recommendation service. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2019, v. 11589, p. 151-159 | en_US |
dcterms.isPartOf | Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) | en_US |
dcterms.issued | 2019 | - |
dc.identifier.scopus | 2-s2.0-85069836447 | - |
dc.relation.conference | International Conference on HCI in Business, Government, and Organizations [HCIBGO] | en_US |
dc.identifier.eissn | 1611-3349 | en_US |
dc.description.validate | 202206 bcfc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | AF-0113 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | This work is supported by the Ministry of Science and Technology of Taiwan (106-2410-H-110-082), and the Intelligent Electronic Commerce Research Center from the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan. | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 25851965 | - |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Jin_Recommendation_As_Service.pdf | Pre-Published version | 860.59 kB | Adobe PDF | View/Open |
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