Engineering Approach to Resource Evaluation for Online Appointment Platforms

The difficulty of resource evaluation lies in obtaining complete product resource data; using Baidu Doctor—a online medical appointment service—as an example, the article explains why comprehensive, high‑quality appointment slots are essential for user acquisition and competitive analysis.

It proposes a generic three‑step framework—capture, parse, compute—where the first step focuses on acquiring competitor data via web pages or APIs, after defining the required metrics and competitor forms.

Key evaluation indicators are introduced, such as coverage (province‑level and hospital‑level), quality (hospital, department, information completeness), and focus hospitals, each with feasibility checks (data availability, volume, interference, timeliness).

Data collection begins with URL analysis to identify the request URLs, asynchronous loading, response formats, and encryption status, ensuring that the target endpoints are reachable and parsable.

Tool selection covers three main options: (1) custom HTTP requests (e.g., PHP curl), (2) public crawling services for large‑scale scraping, and (3) web‑automation frameworks like Selenium for pages requiring JavaScript rendering. Example PHP curl code is shown below:

// Initialize
$ch = curl_init();
// Set options including URL
curl_setopt($ch, CURLOPT_URL, "http://www.baidu.com");
curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
curl_setopt($ch, CURLOPT_HEADER, 0);
// Execute and get HTML content
$output = curl_exec($ch);
// Close handle
curl_close($ch);
// Print data
print_r($output);

Data fetching strategies involve classifying URLs into patterns (e.g., hospital list, hospital detail, shift case) and constructing them programmatically based on parameters such as region and page number.

Parsing is divided into API parsing—using language‑specific JSON libraries—and web page parsing with Python's BeautifulSoup, illustrating steps like creating a soup object, locating elements with findAll , and extracting attributes.

Strategy calculation consists of data preprocessing (aggregating by dimensions like region, resource level, and time) and scoring formulas. Two scoring methods are described: absolute value (product value ÷ full score × weight) and relative value (using comparative ratios across sub‑dimensions). Sample tables demonstrate how scores for multiple products are derived.

The article concludes by summarizing the end‑to‑end workflow for resource data acquisition, analysis, and metric‑driven decision making, inviting readers to discuss further improvements.