This week Sir Tim Bernes-Lee speaks about the intelligent web and the Obama attempts to smarten up its campaign using text analytic technology. Meanwhile, we report on the state of database technology and Robert Cringely makes some Siri-ous claims.
Each week we bring you the most thought-provoking news on how the semantic web is changing the way web users discover, interact and exchange online.
We hope you find the links useful, and if you’d like us to cover any particular aspect of the semantic web in the comments box below.
Our software development future: "probabilistic" applications - Computer Weekly
IBM's Lotusphere conference wrapped up today with an inspirational talk from Sir Tim-Berners Lee who spoke about the need to move to a more intelligent web. Having already spent 20 year working on "engineering" the Internet, Berners-Lee now sees the need to progress to the "semantic web", where computers understand more about the documents and data that we exchange over the wires. Technologies included in this area include: contextual analysis of data - so we know more about what it really means, natural language processing - and text analytics, big data - and workload optimized processing and processing carried out at the Teraflops level of computing. While some may say that this progression towards probabilistic logic is nothing new -- when interplayed and interconnected with the semantic web 3.0 Internet of the future I think it makes interesting food for thought. Probabilisticly at least.
Project Dreamcatcher - How cutting-edge text analytics can help the Obama campaign determine voters’ hopes and fears. – Slate Magazine
The challenge was, in essence, semantic: teaching computers to decode complex product descriptions and isolate their essential attributes. For another client, Ghani, along with four Accenture colleagues and a Carnegie Mellon computer scientist, used a Web crawler to pull product names and descriptions from online clothes stores and built an algorithm that could assess products based on eight different attributes, including “age group,” “formality,” “price point,” and “degree of sportiness.” Once the products had been assigned values in each of those categories, they could be manipulated numerically—the same way that Ghani’s predictive models had tried to make sense of the grocery shopping list. By reducing it to its basic attributes—lightweight mesh nylon material, low profile sole, standard lacing system—a retailer could predict sales for shoes it had never sold before by comparing them to ones it had.
Does Siri infringe old Excite patents? – 9to5mac
Shawn Carolan of Menlo Ventures, an investor in Siri Inc., prior to Apple acquiring the company, recently sat down on Bloomberg to discuss the technology. Apart from talking about the initial demo that attracted him to the investment and meeting Siri Co-Founder Norman Winarsky, Bloomberg host Cory Johnson pressed him on exactly how Siri is able to take voice-recognition data and determine intent. Around the 3:20 mark, Carolan discussed Siri’s unique approach of taking all words as “one big block” and mapping “those strings of words across” a group of 10 domains of expertise. This approach sounds familiar to at least one technology journalist who claimed the method is similar to patents owned by search portal Excite in 1994.
State of Database Technology – Disgruntled and Overcharged - Information Week
In short, the well-established data structures that have served us effectively for more than 40 years are showing their age. Changes to how our organizations use data, as well as the sheer amount of data we manage, have led to new hosting and structuring options, including NoSQL, semantic data stores and hosted warehouse environments. Some of these are gaining traction, while others, unfortunately, remain largely ignored. Sometimes, as with cloud or virtualization, there are good reasons for holding back, but in other cases, particularly lower-cost relational database management systems and moving to commodity hardware, we’re passing on technology that could cut costs while increasing satisfaction.