Evidence map›Paper›PMID 42292859›Full record

ArticleMethodsX2026

Optimizing merchant compliance: A system for product specific rule extraction using NLP.

Atharva Khewalkar, Anuj Walsepatil, Ritesh Phadtare, Sakshi Jadhav, Pratiksha Shinde, Archana Y Chaudhari

Abstract read
In one paragraph

Article in MethodsX, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Atharva KhewalkarDr. D. Y. Patil Institute of Technology, Pimpri, Pune, India.
Anuj WalsepatilDr. D. Y. Patil Institute of Technology, Pimpri, Pune, India.
Ritesh PhadtareDr. D. Y. Patil Institute of Technology, Pimpri, Pune, India.
Sakshi JadhavDr. D. Y. Patil Institute of Technology, Pimpri, Pune, India.
Pratiksha ShindeDr. D. Y. Patil Institute of Technology, Pimpri, Pune, India.
Archana Y ChaudhariSymbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Product quality and safety are crucial in the e-commerce market, particularly for regulated sectors like the food industry, for user protection, and it is the responsibility of the merchants who sell their products to ensure these are maintained. Here comes the role of the government, which lays down certain rules and regulations that need to be followed. These rules and regulations are laid down by the central or state government of India. All these rules are enforced by the authorities established under the respective ministries. All these rules and regulations are maintained in the form of government repositories on the websites of the respective government ministries. Accessing data that is present in these repositories is very difficult for users, as these rules, regulations, and amendments are made available in PDF format to the general public and are often in an unstructured format. This initial study validates the system's effectiveness using the specific domain of Indian food safety regulations. Validation of the system on food-specific regulations demonstrated promising performance, achieving a task accuracy between 82 and 89% over 10 runs and an NLP model F-score of 87.17%. The proposed system makes it easy for users to access this data, allowing them to search for rules and regulations related to their product by providing a search engine. The proposed system gathers data scattered across various websites using web scraping. This data is then automatically cleaned and organized using automation scripts before being presented to the users in a structured and informative format. The proposed system website delivers accurate, real-time data with high speed and reliability, ensuring users get up-to-date and precise information instantly. The proposed system provides product-specific output using NLP (Natural Language Processing).•Ensuring product quality and safety in e-commerce is crucial for user protection, and merchants must maintain these standards. The government enforces rules and regulations through various ministries.•Government rules and regulations are often stored in unstructured PDF formats on ministry websites, making it difficult for users to access and interpret the information.•The proposed system uses web scraping to gather regulatory data, cleans it using automated scripts, and stores it in text format. It employs Spacy natural language processing algorithms to provide product-specific search results.

Indexed as

ExtractionNatural language processingSegmentationSpacyTime optimizationTokenizationWeb scrapping

Identifiers

PMID42292859
PMCPMC13264087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.