DeepPeep

DeepPeep is a search engine that aims to crawl and index every database on the public Web, it is no longer online. Unlike traditional search engines, which crawl existing webpages and their hyperlinks, DeepPeep aims to allow access to the so-called Deep Web, World Wide Web content only available via for instance typed queries into databases. The project started at the University of Utah and was overseen by Juliana Freire, an associate professor at the university's School of Computing WebDB group. The goal is to make 90% of all WWW content accessible, according to Freire. The project ran a beta search engine and was sponsored by the University of Utah and a $243,000 grant from the National Science Foundation. It generated worldwide interest.

Similar to Google, Yahoo, and other search engines, DeepPeep allows the users to type in a keyword and returns a list of links and databases with information regarding the keyword.

However, what separated DeepPeep and other search engines is that DeepPeep uses the ACHE crawler, 'Hierarchical Form Identification', 'Context-Aware Form Clustering' and 'LabelEx' to locate, analyze, and organize web forms to allow easy access to users.

The ACHE Crawler is used to gather links and utilizes a learning strategy that increases the collection rate of links as these crawlers continue to search. What makes ACHE Crawler unique from other crawlers is that other crawlers are focused crawlers that gather Web pages that have specific properties or keywords. Ache Crawlers instead includes a page classifier which allows it to sort out irrelevant pages of a domain as well as a link classifier which ranks a link by its highest relevance to a topic. As a result, the ACHE Crawler first downloads web links that has the higher relevance and saves resources by not downloading irrelevant data.

In order to further eliminate irrelevant links and search results, DeepPeep uses the HIerarchical Form Identification (HIFI) framework that classifies links and search results based on the website's structure and content. Unlike other forms of classification which solely relies on the web form labels for organization, HIFI utilizes both the structure and content of the web form for classification. Utilizing these two classifiers, HIFI organizes the web forms in a hierarchical fashion which ranks the a web form's relevance to the target keyword.

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