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Record W2399734345

Improved Two-Way Bit-parallel Search

2014· article· en· W2399734345 on OpenAlexaff
Branislav Ďurian, Tamanna Chhabra, Sukhpal Singh Ghuman, Tommi Hirvola, Hannu Peltola, Jorma Tarhio

Bibliographic record

VenuePrague Stringology Conference · 2014
Typearticle
Languageen
FieldComputer Science
TopicAlgorithms and Data Compression
Canadian institutionsSheridan College
Fundersnot available
KeywordsString searching algorithmComputer scienceSublinear functionString (physics)AlgorithmBit arrayMatching (statistics)Approximate string matchingBit (key)Pattern matchingTheoretical computer scienceMathematicsDiscrete mathematicsArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

New bit-parallel algorithms for exact and approximate string matching are introduced. TSO is a two-way Shift-Or algorithm, TSA is a two-way Shift-And algorithm, and TSAdd is a two-way Shift-Add algorithm. Tuned Shift-Add is a minimalist improvement to the original Shift-Add algorithm. TSO and TSA are for exact string matching, while TSAdd and tuned Shift-Add are for approximate string matching with k mismatches. TSO and TSA are shown to be linear in the worst case and sublinear in the average case. Practical experiments show that the new algorithms are competitive with earlier algorithms.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0030.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.005

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 head0.027
GPT teacher head0.275
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2014
Admission routes1
Has abstractyes

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