AI Search Dataset
AI topic, query, category, source, demand, trend, and verification fields for research, classification, and retrieval experiments.
FormatsCSV / JSON / XLSX / PDF
RefreshMonthly review
Version1.1
VerifiedSeptember 20, 2026
AI search data is useful when the question is about language, topics, product categories, or changing interest. It is not automatically useful for training a model just because the rows contain AI vocabulary.
The specification keeps that distinction visible. It documents topic observations and labels for research, classification, and retrieval experiments.
Designed For
- AI topic research
- query classification
- trend monitoring
- retrieval evaluation
Coverage
Record unitOne AI topic or query observation
Primary scopeAI products, methods, and market language
Source fieldRequired for every measurement
Time fieldObservation date and last verified date
Field Dictionary
Schema Preview
| Field | Type | Description | Example |
|---|---|---|---|
topic | string | Normalized AI topic or query | synthetic tabular data |
topic_group | string | Applied product or method category | data generation |
source_type | enum | Origin of the observation | search_console |
trend_direction | enum | Movement in the stated window | rising |
last_verified | date | Date the record was checked | 2026-09-20 |
Illustrative Rows
Illustrative AI Research Records
| topic | topic_group | source_type | trend_direction | last_verified |
|---|---|---|---|---|
| synthetic tabular data | data generation | search_console | rising | 2026-09-20 |
| dataset validation tools | data quality | manual_observation | stable | 2026-09-20 |
The rows demonstrate a topic-research schema. They are not a model-training corpus.
Collection And Preparation
- Normalize AI topics while preserving the source wording.
- Separate measured demand or visibility from applied category labels.
- Retain related terms for clustering and retrieval tests.
- Review ambiguous brand, model, and method names before release.
Known Limits
- AI terminology changes quickly and requires frequent verification.
- Demand signals from one source cannot establish full market size.
- The dataset is topic and query research, not a general-purpose training corpus.
- Illustrative rows do not represent licensed production observations.
Useful Applications
- group AI topics
- track source-specific visibility
- build query classifiers
- test retrieval coverage
Change Log
- Added product boundary, field dictionary, illustrative rows, methods, and limits.