Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/33111
Title: | Construction of fast retrieval model of e-commerce supply chain information system based on Bayesian network | Authors: | Kang, Le Chu, Yeping Leng, Kaijun VAN NIEUWENHUYSE, Inneke |
Issue Date: | 2020 | Publisher: | SPRINGER HEIDELBERG | Source: | Information Systems and E-Business Management, 18 (4) , p. 705 -722 | 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. | Notes: | Chu, YP (corresponding author), Hubei Univ Econ, Sch Business Adm, Wuhan, Peoples R China. chuyeping1963@163.com |
Other: | Chu, YP (corresponding author), Hubei Univ Econ, Sch Business Adm, Wuhan, Peoples R China. chuyeping1963@163.com | Keywords: | Fast retrieval model;E-commerce supply chain;Bayesian network | Document URI: | http://hdl.handle.net/1942/33111 | ISSN: | 1617-9846 | e-ISSN: | 1617-9854 | DOI: | 10.1007/s10257-018-00392-6 | ISI #: | WOS:000595877400014 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Kang2020_Article_ConstructionOfFastRetrievalMod.pdf Restricted Access | Published version | 1.66 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.