MétaCan
Menu
Back to cohort
Record W173217944

Second Symposium on the Personal Web

2011· article· en· W173217944 on OpenAlexaff
Mark Chignell, Jim Cordy, Joanna Ng, Yelena Yesha

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWeb Data Mining and Analysis
Canadian institutionsIBM (Canada)University of Toronto
Fundersnot available
KeywordsComputer scienceWorld Wide WebWeb developmentWeb modelingPersonal information managerWeb standardsWeb engineeringMashupWeb serviceWeb 2.0Personal computerContext (archaeology)Personal information managementWeb application securityInformation systemEngineering
DOInot available

Abstract

fetched live from OpenAlex

The goal of the second symposium on Personal Web was to provide a report on further work accomplished aiming towards establishing a new milestone in the evolution of the web. This is a radical change from a fixed, manual, drive-by-click to a malleable, context-aware personal assistant web. This second symposium follows the previous symposium about personal that was hosted by CASCON 2010. The symposium began with a review of Personal Web vision, discussions about the architecture of the Personal Web as well as the way in which Personal Web will change human-computer interaction. Past attempts at making the Web more user-centered, including mashups and scripting, were also noted. The scope for innovative interaction paradigms was also discussed, along with the potential impact that Personal Web may have on the discipline of human-computer interaction. Participants in this second symposium continued to explore the nature of Personal Web as an extension of the current that promotes users from their current state of web workers into web supervisors. This means a much reduced cognitive and working memory load while using the to accomplish goals. Papers presented for the symposium discussed the types of smarter interaction and smarter services (Chignell et al, 2010) that are required to enable Personal Web. Other enabling functions mentioned included associated semantic tools that will allow users of Personal Web to operate in units of intentions, as well as progressing by tasks instead of operating in terms of URLs and logon forms. Also reviewed was the role of predictive analytics for supportive decision making within the context of Personal Web. The presentations examined the role of semantics in Personal Web from a variety of perspectives. Participants at this symposium discussed how to extend the to function as a transparent, integrated, instrumented, intelligent and social system in order to assist individual users with tasks and attend to matters of concern. As part of this discussion some of the presentations considered the supporting technologies required to implicitly discover, gather, aggregate, deliver and recommend data, resources and services from across the web. These integrated elements are able to support the user's own situation and needs. Another key area discussed was the relationship of Personal Web to social media and the users' social milieu, such as sharing discoveries, interactions and states automatically with other members of their social circle. This symposium covered requirements and methodologies for a personalized that also provides cognitive support for users in a way that is intuitive, contextual and socially aware. Technology advances were discussed and not only included enhancing the user's experience with particular server domains at the micro level, but also the melding of resources across multiple server domains at the macro level. The symposium concluded with a discussion about specific applications of Personal Web, in the domains of healthcare, e-Commerce, and business in general.

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 categoriesInsufficient payload (model declined to judge)
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 score0.871
Threshold uncertainty score0.999

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)0.0020.001

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 head0.035
GPT teacher head0.209
Teacher spread0.174 · 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.

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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicWeb Data Mining and AnalysisFrench-language works237,207