Minitrack: E-commerce systems development methodologies
Bibliographic record
Abstract
This minitrack hosts three papers covering different aspects of e-commerce development methodologies from different corners of the world. These papers display the widely different concerns and perspectives that are being used by researchers from around the globe in the area of e-commerce systems development methodologies. The first, 'Interoperability for Accessing DBs by E-commerce Applications' by D.N. Jutla, P. Bodorik and U. Cai of Canada presents a framework for encapsulating the important task of database access from web storefronts. As e-commerce applications proliferate, maintaining the integrity of links from the storefronts to the backend databases becomes important. The work from Jutla, Bodorik and Cai suggests an approach to isolate these links to maintain their integrity. The second, 'Scenario Methods for Viewpoint Integration for e-Business Requirements Engineering' by Jaap Gordijn, Hans de Bruin and Hans Akkermans outlines an innovative approach to address the important task of testing commercial and technical feasibility of new business ideas using scenarios. With the advent of the web, the generation of new ideas has accelerated. The work by Gordijn, de Bruin and Akkermans suggests a high-level approach to testing these ideas using multiple stakeholder perspectives. The third, 'Defining EDI Transactions with UML' by C. Huemer of Austria revisits the now familiar UML technique and the Rational Unified Process for application in the context of EDI Transactions. As the emphasis on business-to-business commerce increases, this work should find application in several instances.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.079 | 0.040 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".