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Crawling the Hidden Web

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TLDR
In this paper, the authors address the problem of designing a crawler capable of extracting content from the hidden web, i.e., the set of web pages reachable purely by following hypertext links, ignoring search forms and pages that require authorization or prior registration.
Abstract
Current-day crawlers retrieve content only from the publicly indexable Web, i.e., the set of Web pages reachable purely by following hypertext links, ignoring search forms and pages that require authorization or prior registration. In particular, they ignore the tremendous amount of high quality content “hidden” behind search forms, in large searchable electronic databases. In this paper, we address the problem of designing a crawler capable of extracting content from this hidden Web. We introduce a generic operational model of a hidden Web crawler and describe how this model is realized in HiWE (Hidden Web Exposer), a prototype crawler built at Stanford. We introduce a new Layout-based Information Extraction Technique (LITE) and demonstrate its use in automatically extracting semantic information from search forms and response pages. We also present results from experiments conducted to test and validate our techniques.

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Serving advertisements based on content

TL;DR: In this article, the authors present a method for placing targeted ads on page on the web (or some other document of any media type) by obtaining content that includes available spots for ads, determining ads relevant to content, and/or combining content with ads determined to be relevant to the content.

Crawling the Hidden Web.

TL;DR: A generic operational model of a hidden Web crawler is introduced and how this model is realized in HiWE (Hidden Web Exposer), a prototype crawler built at Stanford is described.
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References
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Book

Information Retrieval: Data Structures and Algorithms

TL;DR: For programmers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents.
Journal ArticleDOI

Focused crawling: a new approach to topic-specific Web resource discovery

TL;DR: A new hypertext resource discovery system called a Focused Crawler that is robust against large perturbations in the starting set of URLs, and capable of exploring out and discovering valuable resources that are dozens of links away from the start set, while carefully pruning the millions of pages that may lie within this same radius.
Journal ArticleDOI

Accessibility of information on the web

TL;DR: As the web becomes a major communications medium, the data on it must be made more accessible, and search engines need to make the data more accessible.
Journal ArticleDOI

Searching the World Wide Web

TL;DR: The coverage and recency of the major World Wide Web search engines was analyzed, yielding some surprising results, including a lower bound on the size of the indexable Web of 320 million pages.
Journal ArticleDOI

Efficient crawling through URL ordering

TL;DR: In this paper, the authors study in what order a crawler should visit the URLs it has seen, in order to obtain more "important" pages first, and they show that a good ordering scheme can obtain important pages significantly faster than one without.
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