Download - How Google and Microsoft taught search to “understand” the Web Austin Granger Chris Hesemann
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How Google and Microsoft taught search to “understand” the Web
Austin GrangerChris Hesemann
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Knowledge of the Web
• String searching does not always convey the true meaning of content.
• Search by knowledge, not by sub-string matching.
• Extracting and categorizing concepts allows for knowledge-based searching.
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“Web of Concepts”
• Extract raw data (phone numbers, addresses, prices, etc.).
• Link related entities together (e.g., link actor to movie).
• Categorize information about each entity (what does this store sell, what has this author written, how highly are they reviewed?).
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• Search engines discover webpages, parse them into objects and data, process them and store the data, updating existing entries as needed.
• “Concept web” stored in vast databases.– Not traditional databases.– Based on graph theory, not relational model.– Database consists of nodes and links.
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Memory Cloud
• To make this efficient we must traverse the entire graph in milliseconds.
• One solution – “memory cloud.”– Store entire database within memory at all times.
• Example: Google search “blowfish”– Results: Show company, encryption algorithm,
sushi– New results: Suggest “pufferfish”
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Limitations
• Currently only works in English.• Including other languages increases the
complexity exponentially, we’ve got a long way to go.
• Dissecting language to understand searches written in normal language, not just keywords.
The Future of Knowledge Searching