Proceedings of the 10th ACM conference on Electronic commerce
Notice bibliographique
Résumé
These proceedings present the technical contributions to the Tenth ACM Conference on Electronic Commerce EC'09, held during July 6-10, 2009 in Stanford, California, USA. Since its inception in 1999, ACM EC has served as the leading scientific conference on advances in theory, systems, and applications for electronic commerce. The natural focus of the conference is on computer science issues, but the conference is interdisciplinary and addresses many facets of electronic commerce including (1) theory and foundations; (2) languages; (3) automation, personalization, and targeting; (4) security, privacy, encryption, and digital rights; (5) applications and empirical studies; and (6) social and human factors. In addition to the main technical program, EC'09 featured two workshops on Ad Auctions and The Economics of Networks, Systems, and Computation and four tutorials on Convergence of Nash Dynamics: Equilibria and Nearly-Optimal Solutions, A Computational Perspective on Game-Theoretic Solution Concepts, Information Exchange, Bidding Languages and Competition in Sponsored Search, and Mechanism Design in Dynamic Settings. The call for papers attracted 161 submissions from academia and industry around the world, including Africa, Asia, Canada, Europe, the Middle East, and the United States. Each paper was reviewed on average by a total of 6 reviewers, 4 from the program and 2 from the senior program committees respectively, on the basis of scientific novelty, technical quality, and importance to the field. The program committee selected 40 papers for presentation at the conference and most of them are published in the proceedings. At the authors' request, only abstracts for the three remaining papers are included along with pointers to full versions of these working papers. This accommodates the practices of fields outside of computer science in which journal rather than conference publishing is the norm and conference publishing sometimes precludes journal publishing. It is expected that many of the papers in these proceedings will appear in a more polished and complete form in scientific journals in the future. The committee has singled out two papers as co-winners of the outstanding paper award. • Eliciting Truthful Answers to Multiple-Choice Questions, by Nicolas Lambert and Yoav Shoham, Stanford University • An Optimal Lower Bound for Anonymous Scheduling Mechanisms, by Itai Ashlagi, Harvard University, Shahar Dobzinski, Hebrew University and Ron Lavi, Technion The first paper was also named as the winner of the best student paper award. EC '09 also hosted two invited keynote addresses. • Susan Athey, Harvard University and Microsoft (joint with TARK XII) • Michael Moritz, Sequoia Capital EC'09 introduced for the first time in this conference series the two-tier reviewing processing involving 13 senior program committee members and 90 program committee members. We sincerely thank all of them for their hard work in ensuring the quality and fairness of the paper reviewing and final program selection process. We'd like to also thank the authors for their submissions and participation in the feedback.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,011 | 0,009 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,249 | 0,139 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».