GP-Based Approach to Comprehensive Quality-Aware Automated Semantic Web Service Composition
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Wang:2017:SEAL,
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author = "Chen Wang and Hui Ma and Aaron Chen and
Sven Hartmann",
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title = "{GP}-Based Approach to Comprehensive Quality-Aware
Automated Semantic Web Service Composition",
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booktitle = "Proceedings of the 11th International Conference on
Simulated Evolution and Learning, SEAL-2017",
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year = "2017",
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editor = "Yuhui Shi and Kay Chen Tan and Mengjie Zhang and
Ke Tang and Xiaodong Li and Qingfu Zhang and Ying Tan and
Martin Middendorf and Yaochu Jin",
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volume = "10593",
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series = "Lecture Notes in Computer Science",
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pages = "170--183",
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address = "Shenzhen, China",
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month = nov # " 10-13",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-68759-9",
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URL = "https://doi.org/10.1007/978-3-319-68759-9_15",
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DOI = "doi:10.1007/978-3-319-68759-9_15",
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size = "14 pages",
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abstract = "Comprehensive quality-aware semantic web service
composition aims to optimise semantic matchmaking
quality and Quality of service (QoS) simultaneously. It
is an NP-hard problem due to its huge search space.
Therefore, heuristics have to be employed to generate
near-optimal solutions. Existing works employ
Evolutionary Computation (EC) techniques to solve
combinatorial optimisation problems in web service
composition. In particular, Genetic Programming (GP)
has shown its promise. The tree-based representation
used in GP is flexible to represent different
composition constructs as inner nodes, but the semantic
matchmaking information can not be directly obtained
from the representation. To overcome this disadvantage,
we propose a tree-like representation to directly cope
with semantic matchmaking information. Meanwhile, a
GP-based approach to comprehensive quality-aware
semantic web service composition is proposed with
explicit support for our representation. We also design
specific genetic operation that effectively maintain
the correctness of solutions during the evolutionary
process. We conduct experiments to explore the
effectiveness and efficiency of our GP-based approach
using a benchmark dataset with real-world composition
tasks.",
- }
Genetic Programming entries for
Chen Wang
Hui Ma
Aaron Chen
Sven Hartmann
Citations