http://storm.incubator.apache.org/
So, you want to build a recommendation engine? At PredictiveIntent, we had a lot of enquiries from people at companies who were not sure whether to build their own recommendation engine, plug in a lightweight recommendations solution, or dedicate some time to implementing “personalisation” properly. Our advice usually consists of three main points: Focus on your goals – will spending too much time building a recommendation engine take your development cycle off track? The importance of technology – thowing a few lines of Javascript code on a side and manually uploading datafeeds might be sufficient for the time being, but it will restrict you from innovating with recommendations? Don’t underestimate performance – can you support a 99.95% uptime with multiple redundancy systems, 60 millisecond response times, peak loads of >100 transactions per second, and more? However, there are many different variations that fall into two main camps: Recommendations and Personalisation.
Building An Open Source, Distributed Google Clone Disclosure: the writer of this article, Emre Sokullu, joined Hakia as a Search Evangelist in March 2007. The following article in no way represents Hakia's views - it is Emre's personal opinions only. Google is like a young mammoth, already very strong but still growing. Healthy quarter results and rising expectations in the online advertising space are the biggest factors for Google to keep its pace in NASDAQ. But now let's think outside the square and try to figure out a Google killer scenario. You may know that I am obsessed with open source (e.g. my projects openhuman and simplekde), so my proposition will be open source based - and I'll call it Google@Home.
The true grit of IT troubleshooting | Data Center Credit: iStockphoto Troubleshooting brings out the armchair quarterback in most IT pros, especially during emergent and highly visible outages. After all, we love a tough problem, and it's easy to gloss over a situation from a disassociated position and say you could have solved it better, faster, or with less fallout. We even do it to ourselves: How many times have we said that if we only knew then what we know now, we would have done differently? There is no disassociated position when troubleshooting.
Building a recommendation engine, foursquare style Mar 22nd Last summer, foursquare’s employee count had grown a bit beyond our office capacity (as we surged towards 20 employees) and we had people sitting in whatever open space we could find. We were split between floors, parked on folding tables, and crammed into couches and loveseats. In one of those seats, @anoopr was playing around with building a map showing interesting places, which we called “Explore.” Social Networking 3.0: From Self-expression to Group Action My favorite social networking site is one that makes $10B of revenues/year, has no infrastructure costs, and has no salesforce, has no management team. Can you guess which one it is? I can't tell you. It's invite only. You'd know if you knew.
Doubly linked list A doubly-linked list whose nodes contain three fields: an integer value, the link to the next node, and the link to the previous node. The two node links allow traversal of the list in either direction. While adding or removing a node in a doubly-linked list requires changing more links than the same operations on a singly linked list, the operations are simpler and potentially more efficient (for nodes other than first nodes) because there is no need to keep track of the previous node during traversal or no need to traverse the list to find the previous node, so that its link can be modified. Nomenclature and implementation[edit]
Towards a Distributed Internet In preparation for the Contact conference that I am helping to organize this October in NYC, I’ve been in discussion with many different communities about the types of initiatives they would like to bring to the table. The purpose of the event is to ‘realize the true potential of social media,’ and determine what infrastructures need to be in place to enable peer-to-peer commerce, culture, and governance. My goal is to help facilitate these conversations now, so that come October, there is already a higher level of awareness and understanding of these issues, and more connections between groups working on similar objectives.
Joseph Weizenbaum Joseph Weizenbaum (8 January 1923 – 5 March 2008) was a German and American computer scientist and a professor emeritus at MIT. The Weizenbaum Award is named after him. Life and career[edit] Born in Berlin, Germany to Jewish parents, he escaped Nazi Germany in January 1936, emigrating with his family to the United States. He started studying mathematics in 1941 at Wayne University, in Detroit, Michigan. In 1942, he interrupted his studies to serve in the U.S.