1. bookVolume 9 (2019): Edizione 1 (June 2019)
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eISSN
2067-354X
Prima pubblicazione
30 Jul 2019
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2 volte all'anno
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Open Access

Suggest Recommendation for Library Users Using Graphs

Pubblicato online: 20 Mar 2020
Volume & Edizione: Volume 9 (2019) - Edizione 1 (June 2019)
Pagine: 41 - 51
Dettagli della rivista
License
Formato
Rivista
eISSN
2067-354X
Prima pubblicazione
30 Jul 2019
Frequenza di pubblicazione
2 volte all'anno
Lingue
Inglese

[1] Sales force, Product Recommendation Engines to Improve Customer Relationships, https://www.salesforce.com/solutions/industries/retail/resources/product-recommendation-engines, (accessed 16 March 2019).Search in Google Scholar

[2] Microsoft, Create a graph database and run some pattern matching queries using T-SQL,https://docs.microsoft.com/en-us/sql/relational-databases/graphs/sql-graph-sample?view=sql-server-2017, (accessed 16 March 2019)..Search in Google Scholar

[3] Valiance Solutions, RECOMMENDER SYSTEMS 101,https://valiancesolutions.com/recommender-systems-101, (accessed 16 March 2019).Search in Google Scholar

[4] Wikipedia, Cypher Query Language,https://en.wikipedia.org/wiki/Cypher_Query_Language, (accessed 16 March 2019).Search in Google Scholar

[5] Jonathan L. Gross, Jay Yellen (2004). Handbook of Graph Theory, CRC Press10.1201/9780203490204Search in Google Scholar

[6] Junmei Feng, Xiaoyi Fengs, Ning Zhang, Jinye Peng (2018). An improved collaborative filtering method based on similarity, https://doi.org/10.1371/journal.pone.020400310.1371/journal.pone.0204003615295730248112Search in Google Scholar

[7] Guy, N. N. (2017). A Recommender system for rental properties (Thesis). Strathmore UniversitySearch in Google Scholar

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