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Record W2914581845 · doi:10.1145/3099023

Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization

2017· paratext· en· W2914581845 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsPersonalizationSession (web analytics)Computer scienceAdaptation (eye)Field (mathematics)World Wide WebInformation retrievalPsychology

Abstract

fetched live from OpenAlex

Submissions were assigned to 1 TC member and received at least 3 reviews. the initial reviews were submitted, the designated TC facilitated discussion amongst reviewers in order to resolve differences and correct misunderstandings. The TC then provided a recommendation to the Program Chairs. The final decisions were based on these recommendations, the meta-reviews, and reviewer scores. A total of 131 submissions were reviewed. Out of 80 regular paper submissions, 29 were accepted (36% acceptance rate); out of 51 short paper submissions, 11 were accepted (22% acceptance rate). This year, we did not invite regular papers to be published as short papers, but instead invited them to either be included in the main proceedings as extended abstracts, or be published in the adjunct proceedings Late Breaking Results track (LBR). Six of them were published in the LBR track, and a total of 27 extended abstracts are published in the main proceedings. The program also features 3 demos, 3 theory, opinion and reflection papers and 14 late breaking results papers presented in UMAP poster session, which collectively showcase the wide spectrum of novel ideas and latest results in user modeling, adaptation and personalization. We also invited three distinguished keynote speakers, each illustrating significant issues and prospective directions for the field. Pearl Pu, School of Computer and Communication Sciences at EPFL, describes in her talk the various challenges related to understanding, detecting, and visualizing emotions in large text datasets. Jennifer Golbeck, University of Maryland, focuses on how to consider issues of privacy and consent when users cannot explicitly state their preferences, The Creepy Factor, and how to balance users concerns with the benefits personalized technology can offer. Paul De Bra, Eindhoven University of Technology, discusses in his talk After twenty-five years of user modeling and adaptation what makes us UMAP? how the field evolved, insights into where the field is headed, and the hottest topics for exploration. The conference includes a doctoral consortium that provides an opportunity for doctoral students to explore and develop their research interests under the guidance of distinguished scholars. This track received 15 submissions, of which seven were accepted as full papers and six as posters. A set of 8 workshops rounded off the program: EdRecSys: Educational Recommender Systems organized by Kurt Driessens (University of Maastricht, The Netherlands), Irena Koprinska (University of Sydney, Australia), Olga C. Santos (Spanish National University for Distance Education, Spain), Evgueni Smirnov (University of Maastricht, The Netherlands), Kalina Yacef (University of Sydney, Australia), Osmar Zaiane (University of Alberta, Canada) EvalUMAP: Towards Comparative Evaluation in User Modeling, Adaptation and Personalization organized by Owen Conlan, Liadh Kelly, Kevin Koidl, Seamus Lawless, Athanasios Staikopoulos (Trinity College Dublin, Ireland) HAAPIE: Human Aspects in Adaptive and Personalized Interactive Environments organized by Panagiotis Germanakos (SAP SE, Germany), Styliani Kleanthous-Loizou (University of Cyprus, Cyprus), George Samaras (Department of Computer Science, University of Cyprus), Vania Dimitrova (University of Leeds, UK), Ben Steichen (Santa Clara University, USA) PALE: Personalization Approaches in Learning Environments organized by Milos Kravcik (RWTH Aachen University, Germany), Olga C. Santos (UNED,Spain), Jesus G. Boticario (UNED, Spain), Maria Bielikova (FIIT STUBA,Slovakia), Tomas Horvath (Eotvos Lorand University, Budapest, Hungary) PATCH: Personalized Access to Cultural Heritage organized by Liliana Ardissono (University of Torino, Italy), Cristina Gena (University of Torino, Italy), Tsvi Kuflik, (University of Haifa, Israel) SOAP: Surprise, Opposition, and Obstruction in Adaptive and Personalized Systems organized by Peter Knees (Johannes Kepler University Linz, Austria), Kristina Andersen (Studio for Electro Instrumental Music, Amsterdam, the Netherlands), Alan Said (Recorded Future, Gothenburg, Sweden), and Marko Tkalcic (Free University of Bozen-Bolzano, Italy) THUM: Temporal and Holistic User Modeling organized by Cataldo Musto (University of Bari Aldo Moro, Italy), Amon Rapp (University of Torino, Italy), Federica Cena (University of Torino, Italy), Frank Hopfgartner (University of Glasgow), Judy Kay (University of Sidney, Australia), Giovanni Semeraro (University of Bari Aldo Moro, Italy) Veronika Bogina (University of Haifa, Israel), David Konopnicki (IBM Research, Haifa, Israel), Tsvi Kuflik (University of Haifa, Israel), Bamshad Mobasher (DePaul University, Chicago, USA) WPPG: Fifty Shades of Personalization, Workshop on Personalization in Serious and Persuasive Games and Gameful Interactions organized by Elke Mattheiss (Austrian Institute of Technology), Marc Busch (Austrian Institute of Technology), Rita Orji (University of Waterloo, Canada), Gustavo F. Tondello (University of Waterloo, Canada), Andrzej Marczewski (Motivait, UK), Wolfgang Hochleitner (University of Applied Sciences Upper Austria), Michael Lankes (University of Applied Sciences Upper Austria), Manfred Tscheligi (University of Salzburg, Austria). Finally, UMAP hosted two tutorials: Semantics-Aware Techniques for Social Media Analysis, User Modeling, and Recommender Systems (half-day) by Pasquale Lops and Cataldo Musto(University of Bari Aldo Moro, Italy) Designing cross-space learning analytics and personalised support (half-day) by Roberto Martinez-Maldonado (University of Technology Sydney, Australia), Abelardo Pardo (University of Sydney, Australia) and Davinia Hernandez-Leo (Universitat Pompeu Fabra, Spain).

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.129
GPT teacher head0.343
Teacher spread0.214 · 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

Quick stats

Citations20
Published2017
Admission routes1
Has abstractyes

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