ML Anthology

SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition

Rama Akkiraju, Biplav Srivastava, Anca-Andreea Ivan, Richard Goodwin, Tanveer Fathima Syeda-Mahmood
AAAI 2006 pp. 1931-1932
doi:10.1109/icws.2006.119 /aaai/2006/akkiraju2006aaai-semaplan/

Abstract

In this paper, we present a novel algorithm to compose Web services in the presence of semantic ambiguity by combining semantic matching and AI planning algorithms. Specifically, we use cues from domain-independent and domain-specific ontologies to compute an overall semantic similarity score between ambiguous terms. This semantic similarity score is used by AI planning algorithms to guide the searching process when composing services. Experimental results indicate that planning with semantic matching produces better results than planning or semantic matching alone. The solution is suitable for semi-automated composition tools or directory browsers

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Cite

Text

Akkiraju et al. "SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition." AAAI Conference on Artificial Intelligence, 2006. doi:10.1109/icws.2006.119

Markdown

[Akkiraju et al. "SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/akkiraju2006aaai-semaplan/) doi:10.1109/icws.2006.119

BibTeX

@inproceedings{akkiraju2006aaai-semaplan,
  title     = {{SEMAPLAN: Combining Planning with Semantic Matching to Achieve Web Service Composition}},
  author    = {Akkiraju, Rama and Srivastava, Biplav and Ivan, Anca-Andreea and Goodwin, Richard and Syeda-Mahmood, Tanveer Fathima},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2006},
  pages     = {1931-1932},
  doi       = {10.1109/icws.2006.119},
  url       = {https://mlanthology.org/aaai/2006/akkiraju2006aaai-semaplan/}
}