Search has become strangely intimate, a trusted friend pointing you in the right direction […] We once used search engines to look for information, now we use search to find us — what once seemed transactional now seems an extension of ourselves.
[…] in the search of the future that Singhal and his masters of disambiguation are constructing in Mountain View, Google will understand that these things are not simply matching sequences but that they are “things” with an internet life and place and history of their own.
[…] “I don’t think we’ll ever get to the semantic web as it was envisioned — detailed labelling and descriptions of web pages by humans — but we are getting closer to its goal: deep descriptions and understanding of the web, through artificial intelligence and natural language understanding.”
[…] “the future of search is verbs.” People, the argument goes, want search to do things, not just suggest things. With the Knowledge Graph, Google is building a world-historical collection of nouns. But will it help book a restaurant table? Or the cheapest flight? As synonymous as search is with Google, much of our search activity now occurs on apps.
[…] As Battelle notes, “the largest issue with search is that we learned about it when the web was young. When the universe was complete, the entire web was searchable,” he says. “Now our digital lives are utterly fractured — in apps, in walled gardens such as Facebook, across clunky interfaces. Reuniting our digital lives into one platform that is searchable is, to me, the largest problem we face today.”
How can Yahoo! use modeling techniques to make me read their news? Well, the model takes some predictor variables, information about me, in order to build a profile of the user currently browsing their site. This information has been gathered by the website about the readers, and include data such as my location, time in my place and even my gender and my age if I’m a registered Yahoo! user. Other information about my habits online is also useful for the algorithm, particularly the places I’ve visited when I visited Yahoo! in the past, and the stories, the news I’ve already seen today. With this information, the model builds a particular profile around me. Yahoo! can then present a ‘Today Page’ specially fitted for me, by matching my profile with the optimized news and headlines that people like me are clicking on. Don’t forget, the point is to make you click! In order to find the perfect “Today Page” for you, Yahoo! analyzes more than 13 million different combinations of headlines, news, images, stories, photographs and even positions on their website displayed every day. They will show only one from those millions, the one that optimizes the clicks in people like you.
Defense is seeking ways to predict the future by monitoring Twitter, blogs and news, and determining the “frequency of contacts between nodes or clusters.” As networks grow larger and more complex, researchers have found it harder to monitor group behavior. ONR also wants researchers to discover networks that could be hidden within networks, and how information and money flows through a community.
Officials also want tools that fuse and assimilate multiple, incomplete data sets on agriculture, weather, terrain, demographics and economic indicators to find patterns. ONR is especially interested in ways to comb text-based information to provide more nuanced views of how groups, such as terrorists, operate by extrapolating the “stated values and beliefs that motivated behaviors of interest,” “community structure and clusters of social networks” and the level of “emotional support expressed towards topics or persons.
You can become a top coder if you want. But the bigger task is to think about the data like a journalist, rather than an analyst. What’s interesting about these numbers? What’s new? What would happen if I mashed it up with something else? Answering those questions is more important than anything else.
Infographic on infographics (via Infographic / Feel free to use this image anywhere)
McKinsey Report: Are you ready for the era of ‘big data’?
Great study on the opportunity and challenges of Big Data. While every industry can benefit from big data analytics some will more than others:
Quotes from the article:
Over time, we believe big data may well become a new type of corporate asset that will cut across business units and function much as a powerful brand does, representing a key basis for competition. If that’s right, companies need to start thinking in earnest about whether they are organized to exploit big data’s potential and to manage the threats it can pose. Success will demand not only new skills but also new perspectives on how the era of big data could evolve—the widening circle of management practices it may affect and the foundation it represents for new, potentially disruptive business models.
Big data ushers in the possibility of a fundamentally different type of decision making. Using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes. In effect, experimentation can help managers distinguish causation from mere correlation, thus reducing the variability of outcomes while improving financial and product performance.