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Record W1986494226 · doi:10.1109/services.2013.62

PALTask Chat: A Personalized Automated Context Aware Web Resources Listing Tool

2013· article· en· W1986494226 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Text Analysis Techniques
Canadian institutionsUniversity of Victoria
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaUniversity of Victoria
KeywordsComputer scienceWorld Wide WebTask (project management)The InternetContext (archaeology)Listing (finance)Domain (mathematical analysis)User profileMultimediaInformation retrievalHuman–computer interaction

Abstract

fetched live from OpenAlex

With the constant evolution of the Internet, a repetitive and ordinary task such as searching online resources has become more complex due to the amount of web services and formats available (e.g., video, audio, text or images). In order to obtain resources within a specific domain, a user manually performs several tasks, such as navigating through different web services, filtering according to various criteria and selecting the relevant results. However, the insufficient contextual information of the underlying application hampers the user's experience. In this paper, we propose a tool to improve a user's experience by automating the task of retrieving interesting resources in a multi user setting. We apply this approach to a chat scenario where users are exposed to resources that are of common interests by exploiting the users' personal context information.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.745

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 communication0.0000.001
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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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

Citations6
Published2013
Admission routes2
Has abstractyes

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