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http://hdl.handle.net/1942/33111
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DC Field | Value | Language |
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dc.contributor.author | Kang, Le | - |
dc.contributor.author | Chu, Yeping | - |
dc.contributor.author | Leng, Kaijun | - |
dc.contributor.author | VAN NIEUWENHUYSE, Inneke | - |
dc.date.accessioned | 2021-01-19T09:17:20Z | - |
dc.date.available | 2021-01-19T09:17:20Z | - |
dc.date.issued | 2020 | - |
dc.date.submitted | 2021-01-13T14:00:41Z | - |
dc.identifier.citation | Information Systems and E-Business Management, 18 (4) , p. 705 -722 | - |
dc.identifier.uri | http://hdl.handle.net/1942/33111 | - |
dc.description.abstract | Bayesian network is a kind of uncertainty knowledge expression and reasoning tool, and it is an effective means to solve problems in related fields such as information retrieval. Considering the characteristics of e-commerce supply chain supply information and Bayesian network, a cognitive big data analysis method for intelligent information system is designed. The model uses a set of information sample documents to describe the query requirements and the documents to be detected. By calculating the similarity between them, the return results of the general search engine are sorted, thereby retrieving the supply chain supply information required by the user. Through numerical results, the precision of the source information retrieval model based on Bayesian network is also significantly higher than that of the trust network model and the inference network model, and the experimental data shows that the Bayesian network model has better retrieval performance than the trust network model and the inference network model. Therefore, when conducting large-scale e-commerce supply chain supply information collection, Bayesian network-based source information retrieval model is effective. | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER HEIDELBERG | - |
dc.subject.other | Fast retrieval model | - |
dc.subject.other | E-commerce supply chain | - |
dc.subject.other | Bayesian network | - |
dc.title | Construction of fast retrieval model of e-commerce supply chain information system based on Bayesian network | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 722 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 705 | - |
dc.identifier.volume | 18 | - |
local.format.pages | 18 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Chu, YP (corresponding author), Hubei Univ Econ, Sch Business Adm, Wuhan, Peoples R China. | - |
dc.description.notes | chuyeping1963@163.com | - |
dc.description.other | Chu, YP (corresponding author), Hubei Univ Econ, Sch Business Adm, Wuhan, Peoples R China. chuyeping1963@163.com | - |
local.publisher.place | TIERGARTENSTRASSE 17, D-69121 HEIDELBERG, GERMANY | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1007/s10257-018-00392-6 | - |
dc.identifier.isi | WOS:000595877400014 | - |
local.provider.type | wosris | - |
local.uhasselt.uhpub | yes | - |
local.description.affiliation | [Kang, Le; Chu, Yeping; Leng, Kaijun] Hubei Univ Econ, Sch Business Adm, Wuhan, Peoples R China. | - |
local.description.affiliation | [Leng, Kaijun] China Acad Social Sci, Natl Acad Econ Strategy, Beijing, Peoples R China. | - |
local.description.affiliation | [Van Nieuwenhuyse, Inneke] Univ Hasselt, Fac Business Econ, Hasselt, Belgium. | - |
local.uhasselt.international | yes | - |
item.contributor | Kang, Le | - |
item.contributor | Chu, Yeping | - |
item.contributor | Leng, Kaijun | - |
item.contributor | VAN NIEUWENHUYSE, Inneke | - |
item.fullcitation | Kang, Le; Chu, Yeping; Leng, Kaijun & VAN NIEUWENHUYSE, Inneke (2020) Construction of fast retrieval model of e-commerce supply chain information system based on Bayesian network. In: Information Systems and E-Business Management, 18 (4) , p. 705 -722. | - |
item.accessRights | Restricted Access | - |
item.fulltext | With Fulltext | - |
item.validation | ecoom 2021 | - |
crisitem.journal.issn | 1617-9846 | - |
crisitem.journal.eissn | 1617-9854 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Kang2020_Article_ConstructionOfFastRetrievalMod.pdf Restricted Access | Published version | 1.66 MB | Adobe PDF | View/Open Request a copy |
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