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Record W2148545105 · doi:10.1109/wi-iat.2009.114

Query Suggestion by Query Search: A New Approach to User Support in Web Search

2009· article· en· W2148545105 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsUniversity of ReginaUniversity of Alberta
Fundersnot available
KeywordsWeb query classificationWeb search queryComputer scienceInformation retrievalQuery expansionQuery optimizationSet (abstract data type)SargableRank (graph theory)Query languageSearch engineRange (aeronautics)Result setMathematicsProgramming languageCombinatoricsEngineering

Abstract

fetched live from OpenAlex

This paper introduces and analyzes a new approach to query suggestion. After the user issues a query q_0, for every document retrieved in a certain rank range [Theta_1,Theta_2], a query search procedure constructs queries that rank the document high enough for the user to see it. From this set of queries the suggestions to be presented to the user are then selected so as to give the best possible access to the documents that were ranked in [Theta_1,Theta_2] for the user's initial query q_0. This approach turns out to be successful under certain assumptions, which are discussed in this paper.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.756
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.289
Teacher spread0.252 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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