Cloudalicious, graphs of del.icio.us tags over time
Draws graphs of del.icio.us tags over time:
Draws graphs of del.icio.us tags over time:
A huge list of public Web services an extract from the list:
I wish Joshua Schacter would respond to Chris Alden and work out a Rojo flag-to-del.ico.us bridge so I can autopopulate my del.icio.us feed with items.
I responded by saying that it seemed an easy fix for something like Greasemonkey to take care of. Knowing from the same post that Steve is running Firefox on his tablet, Greasemonkey seemed a natural bridge-gap between Rojo and del.icio.us.
At the time I knew some javascript but not enough about Greasemonkey to get my feet wet. But as I used Rojo more and more I began to feel the gap between the two services more and more. I also kept a close eye on Steve’s Shared Stories in Rojo, hoping for some nugget of goodness to pursue, but the list remained empty, and I surmised that Steve might have no reason to share stories in Rojo if he had to put them in del.icio.us separately.
So I sat down and worked out the solution myself and wrote a Greasemonkey script that combines sharing in Rojo with posting to del.icio.us. If you run Firefox and Greasemonkey, use del.icio.us and Rojo, and are interested in unifying the share process in Rojo with the posting process in del.icio.us, this script is for you (at least until Rojo and del.icio.us get their heads together about it).
Why Machine Learning is useful for the Web?
Machine learning is especially useful for applying human-like behavior to sets of data so large that it would be infeasible for humans to do the work. When the Web took off about ten years ago, machine learning acquired a cherished prize: a huge, and ever-growing corpus of data. With billions of pages and counting, the Web is too big for humans to encompass entirely. This is where machine learning comes in.
the machine learning technology can only be as “smart” as the humans who generated the seed set, improving that set will improve the accuracy of the demo.
A Yahoo! Research Labs demo that applies a new twist on search that uses machine learning technology to give you a choice: View Yahoo! Search results sorted according to whether they are more commercial or more informational (i.e., from academic, non-commercial, or research-oriented sources).
You control the slider to decide how you want the results sorted. The midpoint of the slider represents the default setting. In this position, the order of results matches Yahoo! Search web results. As you move the slider right, toward “researching” or left toward “shopping” the results are automatically re-sorted for you.
Commercial implies that the primary purpose of a given page is to sell you something. Informational implies that the primary purpose of the page is to provide information related to your search.
This Mindset demo is an example of machine learning applied to the problem of text classification. Machine learning and text classification are two different fields of technical research that found common cause about ten years ago with the emergence of the Web.
Remember, this demo is a work in progress, put together by scientists to test new ideas and techniques. To start the scoring process, a small team of humans scored pages manually to develop the “seed set” of pages on which machine learning would be based. For the seed set, we didn’t rigorously require everyone to use the same scoring approach, so the scoring results may need some fine-tuning.
Over the weekend Feedster announced that they have joined the tagging revolution. They’re coming at it from a different angle than Technorati Tags, though: Technorati harvests author tags from blog content, while Feedster’s new “Tag This” UI widget allows anonymous reader tagging. While Technorati is now tracking how authors tag their content, Feedster is more interested in what the readers say. Feedster-feeder Scott Rafer invokes Dan Gillmor on this topic: the readers know more than the author.
Feedster ‘Tag This’, and Vague Predictions Regarding the Future of Tagging | the institute of hybernautics Submitted by Brian Del Vecchio on May 24, 2005 - 2:27pm.
There’s a new search engine on the block, and while I appreciate the attitude and some of the aspects of the layout, I’m somewhat distressed by the relevance. The site is called BigClique and it’s available at http://www.bigclique.com .
The site has a simple keyword search on the front page; I do not see a link to search help or to an advanced search panel. (There are links to search interfaces in other languages.) This may be it. I did a search for Cleveland. I was bemused by the search results (more about that momentarily) but I will say this: you will never mistake the ads on BigClique for anything but ads. They are extremely clearly-delineated above, to the side, and below the search results. Now, onto the results themselves…
Blog search engine Blogdigger ( http://www.blogdigger.com ) continues to roll out the specialized search services with the launch of Blogdigger Local. You may access the new service at http://local.blogdigger.com .
It doesn’t matter how brainy you are or how much education you’ve had - you can still improve and expand your mind. Boosting your mental faculties doesn’t have to mean studying hard or becoming a reclusive book worm. There are lots of tricks, techniques and habits, as well as changes to your lifestyle, diet and behaviour that can help you flex your grey matter and get the best out of your brain cells. And here are 11 of them.
Nice Idea, you got aggregated in one page the most popular information you usually spread on different accounts as delicious, Flickr and the like. Maybe it’s still limited in the range of syndicated sources but it’s a good starting idea.
Feedication.com is a web application that acts as your own aggregation service. It is able to fetch and display information about you. It supports syndication with some really popular web applications like 43things, audioscrobbler, del.icio.us and Flickr. We also intend to support more web services in the future.