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On the Use of Web Services in Content Adaptation

2010· book-chapter· en· W2504818824 on OpenAlexaff
Khalil El‐Khatib, Gregor von Bochmann, Abdulmotaleb El-Saddik

Bibliographic record

VenueIGI Global eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicMultimedia Communication and Technology
Canadian institutionsUniversity of OttawaOntario Tech University
Fundersnot available
KeywordsComputer scienceContent adaptationWorld Wide WebAdaptation (eye)InteroperabilityMultimediaThe InternetWeb serviceMulti-frequency networkContext (archaeology)Heterogeneous networkUbiquitous computingTelecommunicationsHuman–computer interaction

Abstract

fetched live from OpenAlex

The tremendous growth of the Internet has introduced a number of interoperability problems for distributed multimedia applications. These problems are related to the heterogeneity of client devices, network connectivity, content formats, and user’s preferences. The challenge is even bigger for multimedia content providers who are faced with the dilemma of finding the combination of different variants of a content to create, store, and send to their subscribers that maximize their satisfaction and hence entice them to come back. In this chapter, the authors will present a framework for trans-coding multimedia streams using an orchestration of Web-services. The framework takes into consideration the profile of communicating devices, network connectivity, exchanged content formats, context description, users’ preferences, and available adaptation services to find a chain of adaptation services that should be applied to the content to make it more satisfactory to clients. The framework was implemented as a core component for an architecture that supports personal and service mobility.

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: Other · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.128
GPT teacher head0.303
Teacher spread0.176 · 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
GenreOther

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

Citations0
Published2010
Admission routes1
Has abstractyes

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