ACHE: web crawler for domain-specific search
ACHE Focused Crawler
ACHE is a focused web crawler. It collects web pages that satisfy some specific criteria, e.g., pages that belong to a given domain or that contain a user-specified pattern. ACHE differs from generic crawlers in the sense that it uses page classifiers to distinguish between relevant and irrelevant pages in a given domain. A page classifier can be defined as a simple regular expression (e.g., that matches every page that contains a specific word) or a machine-learning-based classification model. ACHE also automatically learns how to prioritize links in order to efficiently locate relevant content while avoiding the retrieval of irrelevant pages. While ACHE was originally designed to perform focused crawls, it also supports other crawling tasks, including crawling all pages in a given web site and crawling Dark Web sites (using the TOR protocol).
ACHE supports many features, such as:
- Regular crawling of a fixed list of websites
- Discovery and crawling of new relevant websites through automatic link prioritization
- Configuration of different types of pages classifiers (machine-learning, regex, etc)
- Continuous re-crawling of sitemaps to discover new pages
- Indexing of crawled pages using Elasticsearch
- Web interface for searching crawled pages in real-time
- REST API and web-based user interface for crawler monitoring
- Crawling of hidden services using TOR proxies
