A search agent scours the entire web. Constantly Evolving and Expanding.
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Transcript of A search agent scours the entire web. Constantly Evolving and Expanding.
A search agent scours the entire web. Constantly Evolving and Expanding
Google Amazon Yahoo EBay Wikipedia
Humans see one page in native language Computers see multiple pages in code
Find relevant products Buying websites example Gather all relevant stores (e.g. Amazon,
EBay, Newegg) Relative Product TypesRelevant (page, url, query) ^ offer (page)
Determines link is relevant to search
Relevant text for queries
Query is “laptops” thus Laptop Computers is the category. “Computer” is the super category and “lightweight” is a subcategory
Relevant (page, url, query) E store, home, store E OnlineStores ^ Homepage (store, home) ^ link (url) ^ page = getpage (url)
Name (string, category)Name (“laptops”, Laptop Computers)
After searched complete the next job lies with the comparing agent
Information extracted from pages using wrappers
User-determined qualifiers must be met
Laptop Computers ^ offer E Product Offer ^ screen size ^ screen type ^ memory ^ cpu speed ^ hard drive capactiy ^ price ^ etc.
Comparison
B is better than C making C lower relevance than B
A : 2.4 GHz, 1 GB RAM, 120 GB HDD, $2100B : 2.2 GHz, 512 MB RAM, 80 GB HDD, $1500C : 2.2 GHz, 512 MB RAM, 80 GB HDD, $1600
