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Record W2134386068 · doi:10.1109/ccnc.2007.88

A Framework for Efficient Discovery of Web Services Across Heterogeneous Registries

2007· article· en· W2134386068 on OpenAlexaff
Eyhab Al‐Masri, Qusay H. Mahmoud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWeb serviceComputer scienceWorld Wide WebService-oriented architectureWS-I Basic ProfileWeb modelingService discoveryWS-PolicyWeb developmentThe InternetWeb standardsWeb engineeringWeb application security

Abstract

fetched live from OpenAlex

Growth and propagation of the Internet has been a contributing factor for information overload which acts as a deterrent for quick and easy discovery of information. As Web services proliferate, the same dilemma perceived in the discovery of Web pages will become tangible. Currently, the automatic discovery of Web services, an important capability of service- oriented architecture (SOA), is mainly achieved by performing inquiries to business registries such as the UDDI or ebXML. The ability to discover Web services across multiple heterogeneous registries is becoming a challenging task and raises several issues such as performance, reliability, and robustness. In this paper, we introduce the Web Service Repository Builder (WRSB) that serves as an integrated SOA registry and repository for managing the proliferation of Web services and system artifacts. Specifically, the proposed framework actively captures and navigates among multiple service registries and provides a unified environment for the discovery of Web services. The WSRB framework is compatible with, and can be integrated seamlessly into, the existing infrastructure without any modifications to the existing environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.671

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.282
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations32
Published2007
Admission routes1
Has abstractyes

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