Arabic Search Intent Classifier & Heuristic Taxonomy
Stop misclassifying Arabic queries. Classify Egyptian and Gulf search intents accurately with a zero-dependency Python heuristic engine.
Problem it addresses
Develop a lightweight, dependency-free Python CLI (arabic_intent_classifier.py) that ingests a CSV of Arabic keywords and classifies each query into Informational, Commercial Investigation, Transactional, or Navigational using a dialect-aware heuristic lexicon covering Egyptian, Saudi, and Gulf phrasing. Includes test suite with 100 sample queries.
Who it is for
PRO operating in high-growth e-commerce, digital publishing, and direct-response marketing across Saudi Arabia, UAE, and Egypt.
What is inside
Key files listed in the README repository architecture:
data/intent_lexicon_ar.jsonexamples/classified_output.csvexamples/input_keywords.csvLICENSEREADME.mdsrc/classifier.pytests/test_classifier.py
How to evaluate and use it
- Read the README first and confirm that the documented problem matches your use case.
- Inspect the listed files to find the data, tools, templates, and tests relevant to your task.
- Follow the repository’s Quick Start and check prerequisites before running commands.
- Compare outputs with documented examples and review limitations before using them in a decision or client workflow.
Quick Start from the README: python -m unittest discover -s tests · python src/classifier.py --help
Scope and limitations
- Colloquial Arabic Intent Ambiguity: Informational and commercial intent often overlap in Arabic social queries (e.g., 'كام سعره' vs 'أفضل نوع').
- Transliterated Brand Queries: Queries containing Arabizi or English brand names require phonological normalization prior to intent scoring.
- Local Commercial Heuristics: Keywords containing 'في الرياض' or 'كاش' signal immediate transactional and local purchase intent.
This page summarizes the available documentation; it does not establish performance or business results. Verify data and prerequisites before use.