“In the coming years, we will see a revolution in the ability of machines to access, process, and apply information. This revolution will emerge from three distinct areas of activity connected to the Semantic Web: the Web of Data, the Web of Services, and the Web of Identity providers. These webs aim to make semantic knowledge of data accessible, semantic services available and connectable, and semantic knowledge of individuals processable, respectively. In this post, we will look at the first of these Webs (of Data) and see how making information accessible to machines will transform how we find information.”

I did find the three ‘Webs’ mentioned in their into — data, services and identity providers — to be interesting. The first two are standard components of the envisioned future Web but their third, a web of identity providers, less so. I am unsure its meant to refer to authentication services and protocols (e.g., oauth) or maybe some kind of named entity recognition services from text. The former is certainly necessary for web services and APIs to work more seamlessly, but doesn’t seem to me to be as significant a problem as developing highly interoperable and integrable Webs of data and services. Of course, I am probably unaware of the subtleties involved in getting this right while maintaing security and appropriate privacy. In any case, I look forward to the articles to follow.

“We’re searching Twitter constantly to keep you up to date with the conversation about the IL-5 special election. The graph above lets you track buzz about the candidates over the last two weeks.”

The Windy City Twitter Tracker is probably written to be easily repurposed, judging from the Web site, which describe it as currently tracking the “Race for the 5th”. The mashup is credited to Whattech.

Here’s how the NYT Bits blog described it in Amazon.com Invades the Apple App Store:

“There is, however, one unusual and noteworthy aspect of the app called Amazon Remembers, which Amazon is calling “experimental.” The tool lets users take a photograph of any product they see in the real world. The photos are then uploaded to Amazon and turned over to the far-flung freelance workers in Amazon’s Mechanical Turk program, who will try to match them with products for sale on Amazon.com. The results will not be instantaneous (between 5 minutes and 24 hours, the company says), but the idea is to entice consumers to buy products from Amazon instead of its offline rivals.”

Too bad we are in a recession depression.

“In the mid-1990s a Web search for, say, “DISCOVER magazine” meant wading through thousands of results presented in a very imperfect order. Then, in 1996, 24-year-old Jon Kleinberg developed an algorithm that revolutionized Web search. That is why today, that same search lists this magazine’s home page first. Kleinberg, now 37, created the Hyperlink-Induced Topic Search algorithm, which estimates a Web page’s value in both authority (quality of content and endorsement by other pages) and hub (whether it links to good pages).

Kleinberg continues to combine computer science, data analysis, and sociological research to help create better tools that link social networking sites. He envisions an increase in how we can see information move through space over time, in what he calls geographic hot spots on the Web, based on the interests of a particular region.

Our social network links and friendships depend on these geographic hot spots, Kleinberg says, which makes searching easier by “taking into account not just who and when, but where.” He is now studying how word-of-mouth phenomena like fads and rumors flow through groups of people, hoping to apply this knowledge to processes such as political mobilization.”

“A lot can happen in one year on the Internet, so we thought we’d check back in with each of the 10 products and see how they’re progressing. What’s changed over the past year and what are these companies working on now? The products are, in no particular order: Freebase, Powerset, Twine, AdaptiveBlue, Hakia, Talis, TrueKnowledge, TripIt, Calais (was ClearForest), Spock.”

They plan to publish a completely new list of Semantic applications to watch as the next post in the series and ask people to leave suggestions in the post comments.

Maybe Read/Write Web will do like Michael Apted’s 7up series and report back to us on how the systems are doing each year, which I guess may be like seven Web-years.

“3scale provides a new generation of infrastructure for the web – point and click contract management, monitoring and billing for Web Services. The 3scale platform makes it easy for providers to launch their APIs, manage user access and, if desired, collect usage fees. Service users can discover services they need and sign up for plans on offer.” (source)

They have been operating a private beta system for a few months and just announced that their public beta is open. Currently signing up with 3scale and registering services is free and the only costs are commissions on transaction fees your service charges. Once you’ve registered a service, you can install one of several 3scale plugins for your programming environment to get your service talking to 3scale and configure one or more usage plans. 3scale uses Amazon’s EC2, S3 and Cloud Computing services.

3scale’s co-founder and technical lead is Steve Wilmott, who we worked with for many years when he was an academic doing research on multiagent systems. Several months ago he invited us to add Swoogle’s web service to 3scale’s private beta. We were please with how easy it was and look forward to exploring how else to use 3scale.

A story in yesterday’s Washington Post, Manage Your API Infrastructure With 3scale Networks, has some more information.

• world
• US middle atlantic area
• UMBC neighborhood

You can see that the Google just did a quick drive-by of UMBC.

I also noticed that you can expand the street view to “full screen” and drive around interesting areas, like nearby main street in old ellicott city.

Social Media is changing the way we find information, share knowledge and communicate with each other. The important factor contributing to the growth of these technologies is the ability to easily produce “user-generated content”. Blogs, Twitter, Wikipedia, Flickr and YouTube are just a few examples of Web 2.0 tools that are drastically changing the Internet landscape today. These platforms allow users to produce, annotate and share information with their social network. Their combined content accounts for nearly four to five times that of edited text being produced each day on the Web. Given the vast amount of user-generated content and easy access to the underlying social graph, we can now begin to understand the nature of online communication and collaboration in social applications. This thesis presents a systematic study of the social media landscape through the combined analysis of its special properties, structure and content.

First, we have developed techniques to effectively mine content from the blogosphere. The BlogVox opinion retrieval system is a large scale blog indexing and content analysis engine. For a given query term, the system retrieves and ranks blog posts expressing sentiments (either positive or negative) towards the query terms. We evaluate the system on a large, standard corpus of blogs with available human verified, relevance assessments for opinions. Further, we have developed a framework to index and semantically analyze syndicated feeds from news websites. This system semantically analyzes news stories and build a rich fact repository of knowledge extracted from real-time feeds.

Communities are an essential element of social media systems and detecting their structure and membership is critical in several real-world applications. Many algorithms for community detection are computationally expensive and generally, do not scale well for large networks. In this work we present an approach that benefits from the scale-free distribution of node degrees to extract communities efficiently. Social media sites frequently allow users to provide additional meta-data about the shared resources, usually in the form of tags or folksonomies. We have developed a new community detection algorithm that can combine information from tags and the structural information obtained from the graphs to detect communities. We demonstrate how structure and content analysis in social media can benefit from the availability of rich meta-data and special properties.

Finally, we study social media systems from the user perspective. We present an analysis of how a large population of users subscribes and organizes the blog feeds that they read. It has revealed several interesting properties and characteristics of the way we consume information. With this understanding, we describe how social data can be leveraged for collaborative filtering, feed recommendation and clustering. Recent years have seen a number of new social tools emerge. Microblogging is a new form of communication in which users can describe their current status in short posts distributed by instant messages, mobile phones, email or the Web. We present our observations of the microblogging phenomena and user intentions by studying the content, topological and geographical properties of such communities.

The course of this study spans an interesting period in Web’s history. Social media is connecting people and building online communities by bridging the gap between content production and consumption. Through our research, we have highlighted how social media data can be leveraged to find sentiments, extract knowledge and identify communities. Ultimately, this helps us understand how we communicate and interact in online, social systems.

He argues that shooting for the head (#1) takes too much effort and money, but it doesn’t mean you have to resign yourself to life out on the thin part of the long tail (#3) — you can aim for “profit pocket #2″.