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Record W4390680419 · doi:10.23977/acss.2023.071103

Automobile Marketing System Based on Digital Media Technology and "Internet+" Web Services

2023· article· en· W4390680419 on OpenAlexvenueno aff
Jinhua Li

Bibliographic record

VenueAdvances in Computer Signals and Systems · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicE-commerce and Technology Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsDigital marketingThe InternetBusinessInternet presence managementMarketingMarketing researchReturn on marketing investmentMarketing mix modelingMarketing managementContext (archaeology)Marketing strategyAdvertisingWorld Wide WebComputer scienceMarketing effectiveness

Abstract

fetched live from OpenAlex

With the rapid development of the Internet and digital media technology, a new type of marketing method has emerged - internet marketing. Internet marketing is a new type of marketing method that utilizes digital media interaction to achieve marketing goals. This new type of marketing has unique marketing characteristics such as cross-temporal, high-efficiency, economical, etc, which better meets the information dissemination and exchange between enterprises and individuals. In this context, this article uses Internet technology to design an automobile marketing system based on digital media technology and "Internet +" web services, and conducts functional tests on the system. The results show that the performance of the system meets the standards. The system is applied to the automotive industry and found that the system's sales statistics module can clearly count the company's sales, and pointed out that in 2019, the company's highest sales record was in September, and its sales reached 37.53 million yuan.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.003

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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2023
Admission routes1
Has abstractyes

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