EasySpider: A No-Code Visual System for Crawling the Web
The web is a treasure trove for data that is increasingly used by computer scientists for building large machine learning models as well as non-computer scientists for social studies or marketing analyses. As such, web-crawling is an essential tool for both computational and non-computational scientists to conduct research. However, most of the existing web crawler frameworks and software products either require professional coding skills without an easy-to-use graphic user interface or are expensive and limited in features. They are thus not friendly to newbies and inconvenient for complicated web-crawling tasks. In this paper, we present an easy-to-use visual web crawler system, EasySpider, for designing and executing web crawling tasks without coding. The workflow of a new web crawling task can be visually programmed by following EasySpider’s visual wizard on the target webpages using an intuitive point-and-click interface. The generated crawler task can then be easily invoked locally or as a web service. Our EasySpider is cross-platform and flexible to adapt to different web-resources. It also supports advanced configuration for complicated tasks and extension. The whole system is open-sourced and transparent for free-access at GitHub, which avoids possible privacy leakage.
Code (1)
Tasks
Data IntegrationMarketingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Smart Bilingual Focused Crawling of Parallel Documents
Crawling parallel texts $\unicode{x2014}$texts that are mutual translations$\unicode{x2014}$ from the Internet is usually done following a brute-force approach: documents are massively downloaded in an unguided process, …
Knowledge Graph RAG: Agentic Crawling and Graph Construction in Enterprise Documents
This research paper addresses the limitations of semantic search in complex enterprise document ecosystems. Traditional RAG pipelines often fail to capture hierarchical and interconnected information, leading to retrieva…
Knowledge GraphsThe Synergy of Automated Pipelines with Prompt Engineering and Generative AI in Web Crawling
Web crawling is a critical technique for extracting online data, yet it poses challenges due to webpage diversity and anti-scraping mechanisms. This study investigates the integration of generative AI tools Claude AI (So…
DiversityPrompt EngineeringXPath Agent: An Efficient XPath Programming Agent Based on LLM for Web Crawler
We present XPath Agent, a production-ready XPath programming agent specifically designed for web crawling and web GUI testing. A key feature of XPath Agent is its ability to automatically generate XPath queries from a se…
Document Quality Scoring for Web Crawling
The internet contains large amounts of low-quality content, yet users expect web search engines to deliver high-quality, relevant results. The abundant presence of low-quality pages can negatively impact retrieval and cr…