Service2vec: a vector representation for web services

Yuqun Zhang; Mengshi Zhang; Xi Zheng; Dewayne E. Perry

doi:10.1109/ICWS.2017.114

Service2vec: a vector representation for web services

Yuqun Zhang, Mengshi Zhang, Xi Zheng, Dewayne E. Perry

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

4 Citations (Scopus)

Abstract

Among the approaches that investigate the similarity between web services, hardly any concentrates on the impacts from contexts. In this paper we introduce service2vec which is an approach to represent web services as service embeddings based on a recent popular deep learning technique word2vec. Our approach composes and combines web services to be a document that is trained by the modeling technique of word2vec. As a result, each web service in the document is vectorized. By taking the advantage of word2vec, the resulting service embeddings of service2vec can be used to illustrate the contextual relations between web services. The experimental results suggest that service2vec can deliver contextual similarity between web services.

Original language	English
Title of host publication	ICWS 2017
Subtitle of host publication	Proceedings of 2017 IEEE 24th International Conference on Web Services
Editors	Shiping Chen, Ilkay Altintas
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	890-893
Number of pages	4
ISBN (Electronic)	9781538607527
ISBN (Print)	9781538607534
DOIs	https://doi.org/10.1109/ICWS.2017.114
Publication status	Published - 2017
Externally published	Yes
Event	24th IEEE International Conference on Web Services, ICWS 2017 - Honolulu, United States Duration: 25 Jun 2017 → 30 Jun 2017

Conference

Conference	24th IEEE International Conference on Web Services, ICWS 2017
Country/Territory	United States
City	Honolulu
Period	25/06/17 → 30/06/17

Keywords

contextual similarity
service composition
word2vec

Access to Document

10.1109/ICWS.2017.114

Cite this

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title = "Service2vec: a vector representation for web services",

abstract = "Among the approaches that investigate the similarity between web services, hardly any concentrates on the impacts from contexts. In this paper we introduce service2vec which is an approach to represent web services as service embeddings based on a recent popular deep learning technique word2vec. Our approach composes and combines web services to be a document that is trained by the modeling technique of word2vec. As a result, each web service in the document is vectorized. By taking the advantage of word2vec, the resulting service embeddings of service2vec can be used to illustrate the contextual relations between web services. The experimental results suggest that service2vec can deliver contextual similarity between web services.",

keywords = "contextual similarity, service composition, word2vec",

author = "Yuqun Zhang and Mengshi Zhang and Xi Zheng and Perry, {Dewayne E.}",

year = "2017",

doi = "10.1109/ICWS.2017.114",

language = "English",

isbn = "9781538607534",

pages = "890--893",

editor = "Shiping Chen and Ilkay Altintas",

booktitle = "ICWS 2017",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "24th IEEE International Conference on Web Services, ICWS 2017 ; Conference date: 25-06-2017 Through 30-06-2017",

}

Zhang, Y, Zhang, M, Zheng, X & Perry, DE 2017, Service2vec: a vector representation for web services. in S Chen & I Altintas (eds), ICWS 2017: Proceedings of 2017 IEEE 24th International Conference on Web Services. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 890-893, 24th IEEE International Conference on Web Services, ICWS 2017, Honolulu, United States, 25/06/17. https://doi.org/10.1109/ICWS.2017.114

Service2vec: a vector representation for web services. / Zhang, Yuqun; Zhang, Mengshi; Zheng, Xi et al.
ICWS 2017: Proceedings of 2017 IEEE 24th International Conference on Web Services. ed. / Shiping Chen; Ilkay Altintas. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 890-893.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Service2vec

T2 - 24th IEEE International Conference on Web Services, ICWS 2017

AU - Zhang, Yuqun

AU - Zhang, Mengshi

AU - Zheng, Xi

AU - Perry, Dewayne E.

PY - 2017

Y1 - 2017

N2 - Among the approaches that investigate the similarity between web services, hardly any concentrates on the impacts from contexts. In this paper we introduce service2vec which is an approach to represent web services as service embeddings based on a recent popular deep learning technique word2vec. Our approach composes and combines web services to be a document that is trained by the modeling technique of word2vec. As a result, each web service in the document is vectorized. By taking the advantage of word2vec, the resulting service embeddings of service2vec can be used to illustrate the contextual relations between web services. The experimental results suggest that service2vec can deliver contextual similarity between web services.

AB - Among the approaches that investigate the similarity between web services, hardly any concentrates on the impacts from contexts. In this paper we introduce service2vec which is an approach to represent web services as service embeddings based on a recent popular deep learning technique word2vec. Our approach composes and combines web services to be a document that is trained by the modeling technique of word2vec. As a result, each web service in the document is vectorized. By taking the advantage of word2vec, the resulting service embeddings of service2vec can be used to illustrate the contextual relations between web services. The experimental results suggest that service2vec can deliver contextual similarity between web services.

KW - contextual similarity

KW - service composition

KW - word2vec

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U2 - 10.1109/ICWS.2017.114

DO - 10.1109/ICWS.2017.114

M3 - Conference proceeding contribution

SN - 9781538607534

SP - 890

EP - 893

BT - ICWS 2017

A2 - Chen, Shiping

A2 - Altintas, Ilkay

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

Y2 - 25 June 2017 through 30 June 2017

ER -

Service2vec: a vector representation for web services

Abstract

Conference

Keywords

Access to Document

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