The Intelligent Web: Search, smart algorithms, and big data

The Intelligent Web: Search, smart algorithms, and big data

Gautam Shroff

Language: English

Pages: 256

ISBN: 0199646716

Format: PDF / Kindle (mobi) / ePub


As we use the Web for social networking, shopping, and news, we leave a personal trail. These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of "Web intelligence", as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.

Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

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customer clicks their ad, regardless of whether that click gets converted to a sale. At the same time, the advertiser does not pay if a ∗ . 49 THE INTELLIGENT WEB customer merely looks at the ad, without clicking it. The PPC model was first invented by Bill Gross who started GoTo.com in 1998. But it was Google that made PPC really work by figuring out the best way to charge for ads in this model. In the PPC model, the mutual information between the potential buyer and

multiplication tables’. The easy case just discussed was where we could find an exact match from our past experience. However, what if we found many exact matches, and they did not all have the same animal label? Chihuahuas could be a reason why; after all, apart from being small and having rounder heads than other dogs, many of them do come fairly close to meowing. Well, we might decide to choose the majority label again, just as in the case of KNN. What we are doing here, albeit indirectly, is

professor at the Indian Institute of Technology in Kanpur. Studies have shown that 4–7-month-old babies can distinguish foreground and background, identify distinct objects, and direct their attention based on visible motion. They understand occlusion, i.e., ‘are surprised by a tall object disappearing behind a short barrier [i.e., one too short to actually 129 THE INTELLIGENT WEB occlude it]’.60 They can also ‘understand’ that one object is ‘contained in’ another, but only later, at 7 months

and reasoning is one of the key tools we employ for ‘connecting the dots’ and making sense of our world. We celebrate reasoning prowess: those who reason better and faster are considered more intelligent than 134 CONNECT others. ‘From a drop of water, a logician could infer the possibility of an Atlantic or a Niagara without having seen or heard of one or the other. So all life is a great chain, the nature of which is known whenever we are shown a single link of it,’ writes the legendary

deciding whether to send the mail to Amy? More importantly, how should Siri go about this reasoning problem? Siri wants to find out if anyone is friends with someone whom we have blocked, and avoid sending the email to that person. In the language of reasoning, Siri needs to check if the following logical statement is true for some X and Y, or show that it is always false: X is a friend AND X is a friend of Y AND Y is blocked. At its disposal Siri has the following facts in its knowledge base,

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