Mining service abstractions (NIER track)

Dionysis Athanasopoulos; Apostolos V. Zarras; Panos Vassiliadis; Valerie Issarny

doi:10.1145/1985793.1985954

Mining service abstractions (NIER track)

Dionysis Athanasopoulos^*
, Apostolos V. Zarras
, Panos Vassiliadis
, Valerie Issarny

^*Corresponding author for this work

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

9 Citations (Scopus)

Abstract

Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.

Original language	English
Title of host publication	ICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference
Pages	944-947
Number of pages	4
DOIs	https://doi.org/10.1145/1985793.1985954
Publication status	Published - 07 Jul 2011
Externally published	Yes
Event	33rd International Conference on Software Engineering, ICSE 2011 - Waikiki, Honolulu, HI, United States Duration: 21 May 2011 → 28 May 2011

Conference

Conference	33rd International Conference on Software Engineering, ICSE 2011
Country/Territory	United States
City	Waikiki, Honolulu, HI
Period	21/05/2011 → 28/05/2011

Keywords

abstraction recovery
agglomerative clustering
services

ASJC Scopus subject areas

Software

Access to Document

10.1145/1985793.1985954

Cite this

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title = "Mining service abstractions (NIER track)",

abstract = "Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.",

keywords = "abstraction recovery, agglomerative clustering, services",

author = "Dionysis Athanasopoulos and Zarras, \{Apostolos V.\} and Panos Vassiliadis and Valerie Issarny",

year = "2011",

month = jul,

day = "7",

doi = "10.1145/1985793.1985954",

language = "English",

isbn = "9781450304450",

pages = "944--947",

booktitle = "ICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference",

note = "33rd International Conference on Software Engineering, ICSE 2011 ; Conference date: 21-05-2011 Through 28-05-2011",

}

Athanasopoulos, D, Zarras, AV, Vassiliadis, P & Issarny, V 2011, Mining service abstractions (NIER track). in ICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference. pp. 944-947, 33rd International Conference on Software Engineering, ICSE 2011, Waikiki, Honolulu, HI, United States, 21/05/2011. https://doi.org/10.1145/1985793.1985954

TY - GEN

T1 - Mining service abstractions (NIER track)

AU - Athanasopoulos, Dionysis

AU - Zarras, Apostolos V.

AU - Vassiliadis, Panos

AU - Issarny, Valerie

PY - 2011/7/7

Y1 - 2011/7/7

N2 - Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.

AB - Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.

KW - abstraction recovery

KW - agglomerative clustering

KW - services

UR - https://www.scopus.com/pages/publications/79959910637

U2 - 10.1145/1985793.1985954

DO - 10.1145/1985793.1985954

M3 - Conference contribution

AN - SCOPUS:79959910637

SN - 9781450304450

SP - 944

EP - 947

BT - ICSE 2011 - 33rd International Conference on Software Engineering, Proceedings of the Conference

T2 - 33rd International Conference on Software Engineering, ICSE 2011

Y2 - 21 May 2011 through 28 May 2011

ER -

Mining service abstractions (NIER track)

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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