Distributed Web Crawler for Topic-Based Content Aggregation
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Solution Overview
Problem
Conventional web crawling techniques are inefficient, accessing only the surface web and providing limited information, with noise and redundancy, and are time-consuming due to centralized architectures, failing to effectively extract relevant deep web content.
Innovation Solution
A method and system for topic-based aggregation of web content that involves receiving Uniform Resource Identifiers, crawling web locations, generating electronic record files with meta-information, identifying and processing elements to extract topic-based content and operational data, and aggregating it into a database, utilizing a distributed architecture for faster and more efficient information retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional centralized web crawling is used, then the system structure is simple, but the crawling speed and information extraction efficiency are low
Solution Approach 1:
The patent divides the centralized web crawling system into multiple distributed crawling nodes that operate independently. Each node crawls specific web pages and extracts information autonomously, then results are aggregated centrally. This segmentation enables parallel processing, significantly increasing crawling speed while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent transitions from a single-dimensional centralized crawling architecture to a multi-dimensional distributed architecture where crawling operations occur across multiple nodes simultaneously. This dimensional expansion allows the system to access and process web content from multiple sources in parallel, dramatically improving productivity without proportionally increasing coordination complexity.
2Loss of information
If conventional web crawling accesses only surface web, then the crawling process is simple and fast, but the information completeness and depth are limited
Solution Approach 1:
The patent implements preliminary indexing and categorization of web pages during the crawling process. By pre-organizing content and identifying deep web resources in advance, the system can efficiently navigate to relevant information without exhaustive searching, reducing time loss while ensuring comprehensive information collection from both surface and deep web layers.
Solution Approach 2:
The patent introduces intermediary indexing structures and metadata layers that bridge surface web accessibility with deep web content. These intermediaries enable the crawler to efficiently locate and access deep web resources without direct complex navigation, maintaining crawling speed while expanding information completeness across web depths.
3Reliability
If conventional web crawling extracts all web content, then the data volume is large, but the data quality and relevance are low due to noise and redundancy
Solution Approach 1:
The patent extracts only relevant information elements from crawled web pages based on predefined criteria and topic models. Instead of collecting all content, the system selectively extracts meaningful data points, eliminating noise and redundancy at the extraction stage. This reduces data volume and improves quality without requiring complex post-processing filtering mechanisms.
Solution Approach 2:
The patent applies different extraction rules and processing strategies to different types of web content based on their local characteristics. By tailoring extraction methods to specific content types and relevance criteria, the system maintains high data quality while simplifying processing complexity through context-appropriate handling rather than uniform complex processing.
4Ease of operation
If conventional web crawling stores information without sorting, then the storage process is simple and fast, but the data organization and usability are poor
Solution Approach 1:
The patent performs preliminary sorting, categorization, and tagging of crawled information during the extraction phase. By organizing data with metadata and hierarchical structures before storage, the system ensures high usability without requiring complex retrieval and reorganization processes later. This preliminary structuring simplifies subsequent data operations while maintaining ease of use.
Data Source
AI summary
A method and a system for performing topic-based aggregation of web content. The method includes receiving a plurality of Uniform Resource Identifiers, wherein each of the plurality of Uniform Resource Identifiers points to a web location related to a subject-matter; crawling the web location, to fetch web content related to the subject-matter, wherein the web content includes one or more elements; generating an electronic record file for storing the web content, and meta-information associated with the crawling of the web location; identifying a first type and at least a second type of the one or more elements; processing the first type of element to obtain a topic-based web content corresponding to a category associated with the subject-matter, and the at least one second type of element to obtain operational data; and aggregating the topic-based web content into a database.