Deep-web crawl is concerned with the problem of surfacing hidden
\ncontent behind search interfaces on the Web. While many
\ndeep-web sites maintain document-oriented textual content (e.g.,
\nWikipedia, PubMed, Twitter, etc.), which has traditionally been the
\nfocus of the deep-web literature, we observe that a significant portion
\nof deep-web sites, including almost all online shopping sites,
\ncurate structured entities as opposed to text documents. Although
\ncrawling such entity-oriented content is clearly useful for a variety
\nof purposes, existing crawling techniques optimized for document
\noriented content are not best suited for entity-oriented sites. In this
\nwork, we describe a prototype system we have built that specializes
\nin crawling entity-oriented deep-web sites. We propose techniques
\ntailored to tackle important subproblems including query generation,
\nempty page filtering and URL deduplication in the specific
\ncontext of entity oriented deep-web sites. These techniques are experimentally
\nevaluated and shown to be effective.<\/p>\n","protected":false},"excerpt":{"rendered":"
Deep-web crawl is concerned with the problem of surfacing hidden content behind search interfaces on the Web. While many deep-web sites maintain document-oriented textual content (e.g., Wikipedia, PubMed, Twitter, etc.), which has traditionally been the focus of the deep-web literature, we observe that a significant portion of deep-web sites, including almost all online shopping sites, 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