Centralized Web Crawling for Data Enrichment and Lower Network Traffic
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Solution Overview
Problem
Current web crawler systems face challenges such as increased security risks, network congestion, and inefficient data processing due to multiple crawlers accessing web servers, which is particularly problematic in real-time or near real-time environments like digital advertising.
Innovation Solution
A centralized crawler system (CCS) that uniformly distributes crawled data to multiple entities, processes data points using machine learning algorithms to identify main elements, and generates enriched data points through external data analysis systems, reducing the need for direct crawler connections and minimizing network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple crawlers directly connect to publishers to collect webpage data, then data collection capability is improved, but security risks and network congestion increase
Solution Approach 1:
The patent introduces a centralized crawler system as an intermediary between publishers and individual data consumers. This mediator collects webpage data once and distributes it to multiple entities, eliminating the need for multiple crawlers to directly connect to publishers. The intermediary approach reduces security risks by limiting direct access points while maintaining data collection capability.
2Productivity
If multiple crawlers directly connect to publishers to collect webpage data, then data collection capability is improved, but network traffic and server load increase
Solution Approach 1:
The patent merges multiple data collection operations into a single centralized crawler system. Instead of multiple crawlers independently querying publishers, the system consolidates these requests into one unified collection process, then distributes the gathered data to multiple consumers. This combining approach significantly reduces network traffic and server load while maintaining comprehensive data collection.
3Productivity
If multiple crawlers access web servers simultaneously, then data collection coverage is improved, but transmission rate decreases due to congestion
Solution Approach 1:
The patent segments the data distribution process after centralized collection. The centralized crawler gathers data once and then segments and distributes it to multiple entities simultaneously. This segmentation allows comprehensive data collection coverage while maintaining high transmission rates by avoiding concurrent access bottlenecks at the publisher level.
4Adaptability or versatility
If individual crawlers are created for each party to collect website information, then customization and control are improved, but system complexity and infrastructure requirements increase
Solution Approach 1:
The patent creates a universal centralized crawler system that serves multiple purposes for different data consumers. This single system performs data collection, parsing, and distribution for various parties, eliminating the need for separate customized crawlers for each entity. The universal approach reduces system complexity while maintaining adaptability through configurable data collection and distribution parameters.
Data Source
AI summary
A system and method for centralized crawling and extracting data points of a webpage using a centralized crawler system is provided. The method includes crawling requested webpage data, wherein the requested webpage data is selected based on a plurality of rules and includes a hypertext markup language (HTML) layer and metadata of a requested webpage; extracting at least one data point that indicate a main element that describes contents of the requested webpage; generating at least one enriched data point that provides additional information on the at least one extracted data point, wherein the additional information is collected from a plurality of data analysis systems (DASs); and creating a structured dataset of the requested webpage data based on the at least one extracted data point.


