Similar Products

Overview Description

The Similar Products feature allows users to identify and view products that share similarities with those in the selected dataset. This functionality helps users discover related products, competitive alternatives, or complementary items based on various similarity metrics. By analyzing product attributes, reviews, and market positioning, the system can identify meaningful product relationships that aid in competitive analysis and market research.

This feature requires a valid dataset containing product information and is particularly useful for market comparison, product planning, and identifying gaps in product offerings.

Swagger Link

API: Similar Products API

Case Documentation

Case 1: Similar Products

Description

User successfully retrieves a list of products similar to those in the selected dataset.

Sequence Diagram

sequenceDiagram
    participant User
    participant API as ProductAnalyzerController
    participant Service as ProductAnalysisService
    participant Repo as WishlistDatasetHistoryRepository
    participant JP as JP API

    Note over User,JP: Step 1: Request Similar Products
    User->>API: GET /api/v1/general/analyzer/{wldh_slug}/products/similar (with parameters)
    
    Note over API,Repo: Step 2: Validate Dataset
    API->>Repo: findBySlug(wldh_slug)
    Repo-->>API: wishlistDatasetHistory
    
    Note over API,Service: Step 3: Retrieve Similar Products
    API->>Service: getSimilarProducts(dataset_id, request_data)
    Service->>JP: Query for similar products
    JP-->>Service: Raw similar products data
    
    Note over Service,API: Step 4: Process Similarity Data
    Service-->>API: Processed similar products
    
    Note over API,User: Step 5: Return Response
    API-->>User: 200 OK (Similar products data)

Steps

Step 1: Request Similar Products

Description: User makes a request to retrieve similar products for a dataset
Request: GET /api/v1/general/analyzer/{wldh_slug}/products/similar
Parameters:
- Path parameter: wldh_slug - unique identifier for the dataset history
- Query parameters:
  - product_id - specific product to find similarities for (optional)
  - similarity_threshold - minimum similarity score (optional)
  - limit - maximum number of similar products to return (optional)

Step 2: Validate Dataset

Description: System validates that the requested dataset exists
Action: Find dataset by slug in the repository
Potential errors: Dataset not found

Step 3: Retrieve Similar Products

Description: System searches for products similar to those in the dataset
Action: Call service method to get similar products
Similarity factors considered:
- Product category
- Price range
- Feature set
- Review content similarity
- Target market

Step 4: Process Similarity Data

Description: System processes and formats similarity data
Action: Sort products by similarity score and prepare response
Processing:
- Calculate similarity metrics
- Include similarity factors
- Apply requested filters

Step 5: Return Response

Description: System returns similar products data to user
Response:
- Success: 200 OK with similar products data
- Error: Appropriate error message and status code

Database Related Tables & Fields

View: Analysis API Spectification

Error Handling

Log
- Similar products retrieval failures logged to application log

Error Detail:

Status Code	Error Message	Description
404	"Dataset not found"	When the specified dataset slug does not exist
400	"Invalid parameters"	When provided parameters don't meet validation requirements
500	Generic error with exception message	When unexpected errors occur during processing

Additional Notes

Similarity calculations may be computationally intensive for large datasets
Consider caching similarity results for performance improvement
The similarity algorithm considers both product attributes and review content for more accurate matches
Similarity scores range from 0.0 to 1.0, with higher scores indicating greater similarity

02.similar-products