Integrating Binary Similarity Measures in the Link Prediction Task

Alfredo Milani; Valentina Franzoni; Giulio Biondi; Yuanxi Li

doi:10.1109/CISP-BMEI.2018.8633089

Integrating Binary Similarity Measures in the Link Prediction Task

Alfredo Milani, Valentina Franzoni, Giulio Biondi, Yuanxi Li

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

In this work we investigate the applicability of binary similarity and distance measures in the context of Link Prediction. Neighbourhood-based similarity measures to assess the similarity of nodes in a network have been long available. They boast the main advantage of low calculation complexity, because only a local view of the network is required. Neighbourhood-based measures are used in a variety of Link Prediction applications, including bioinformatics, bibliographic networks and recommender systems. It is possible to use binary measures in the same context, retaining the same prerogatives and possibly increasing the link prediction performances in domain-specific tasks. Preliminary studies have also been conducted on widely-accepted data sets.

Original language	English
Title of host publication	Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
Editors	Wei Li, Qingli Li, Lipo Wang
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	9781538676042, 9781538676035
ISBN (Print)	9781538676059
DOIs	https://doi.org/10.1109/CISP-BMEI.2018.8633089
Publication status	Published - 13 Oct 2018
Event	11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 - Beijing, China Duration: 13 Oct 2018 → 15 Oct 2018

Publication series

Name	Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI

Conference

Conference	11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
Country/Territory	China
City	Beijing
Period	13/10/18 → 15/10/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/CISP-BMEI.2018.8633089

Cite this

Milani, A., Franzoni, V., Biondi, G., & Li, Y. (2018). Integrating Binary Similarity Measures in the Link Prediction Task. In W. Li, Q. Li, & L. Wang (Eds.), Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 (Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI). IEEE. https://doi.org/10.1109/CISP-BMEI.2018.8633089

Milani, Alfredo ; Franzoni, Valentina ; Biondi, Giulio et al. / Integrating Binary Similarity Measures in the Link Prediction Task. Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. editor / Wei Li ; Qingli Li ; Lipo Wang. IEEE, 2018. (Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI).

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title = "Integrating Binary Similarity Measures in the Link Prediction Task",

abstract = "In this work we investigate the applicability of binary similarity and distance measures in the context of Link Prediction. Neighbourhood-based similarity measures to assess the similarity of nodes in a network have been long available. They boast the main advantage of low calculation complexity, because only a local view of the network is required. Neighbourhood-based measures are used in a variety of Link Prediction applications, including bioinformatics, bibliographic networks and recommender systems. It is possible to use binary measures in the same context, retaining the same prerogatives and possibly increasing the link prediction performances in domain-specific tasks. Preliminary studies have also been conducted on widely-accepted data sets.",

author = "Alfredo Milani and Valentina Franzoni and Giulio Biondi and Yuanxi Li",

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Milani, A, Franzoni, V, Biondi, G & Li, Y 2018, Integrating Binary Similarity Measures in the Link Prediction Task. in W Li, Q Li & L Wang (eds), Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI, IEEE, 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018, Beijing, China, 13/10/18. https://doi.org/10.1109/CISP-BMEI.2018.8633089

Integrating Binary Similarity Measures in the Link Prediction Task. / Milani, Alfredo; Franzoni, Valentina; Biondi, Giulio et al.
Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. ed. / Wei Li; Qingli Li; Lipo Wang. IEEE, 2018. (Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Integrating Binary Similarity Measures in the Link Prediction Task

AU - Milani, Alfredo

AU - Franzoni, Valentina

AU - Biondi, Giulio

AU - Li, Yuanxi

PY - 2018/10/13

Y1 - 2018/10/13

N2 - In this work we investigate the applicability of binary similarity and distance measures in the context of Link Prediction. Neighbourhood-based similarity measures to assess the similarity of nodes in a network have been long available. They boast the main advantage of low calculation complexity, because only a local view of the network is required. Neighbourhood-based measures are used in a variety of Link Prediction applications, including bioinformatics, bibliographic networks and recommender systems. It is possible to use binary measures in the same context, retaining the same prerogatives and possibly increasing the link prediction performances in domain-specific tasks. Preliminary studies have also been conducted on widely-accepted data sets.

AB - In this work we investigate the applicability of binary similarity and distance measures in the context of Link Prediction. Neighbourhood-based similarity measures to assess the similarity of nodes in a network have been long available. They boast the main advantage of low calculation complexity, because only a local view of the network is required. Neighbourhood-based measures are used in a variety of Link Prediction applications, including bioinformatics, bibliographic networks and recommender systems. It is possible to use binary measures in the same context, retaining the same prerogatives and possibly increasing the link prediction performances in domain-specific tasks. Preliminary studies have also been conducted on widely-accepted data sets.

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T3 - Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI

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Milani A, Franzoni V, Biondi G, Li Y. Integrating Binary Similarity Measures in the Link Prediction Task. In Li W, Li Q, Wang L, editors, Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018. IEEE. 2018. (Proceedings - International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI). doi: 10.1109/CISP-BMEI.2018.8633089

Integrating Binary Similarity Measures in the Link Prediction Task

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