How I read PDFs now January 25, 2010
Posted by wanderlust in websites and tips.Tags: adobe, mobipocket, pdf, readability, speed reading
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I find I have a lot to read these days. Mostly electronic stuff. And I can’t/don’t always print things out.
I would love an Amazon Kindle, but almost everything I read is in .pdf format. And I like writing notes on paper, or if I’m reading on my laptop, I use OneNote or Tomboy Notes.
Of late, I tried out speed-reading techniques, and found that I read best when I’m able to look at the entire page at one shot. The problem with trying to do that on Adobe Reader is that if you view the entire page at one shot, the font size is too small to read without squinting.
So. What I do now is to flip the screen by ninety degrees. Ctrl-Alt-leftArrow. I get the same feel as reading a book, my finger running down the page, as is recommended for speed reading. I’m just surprised it took me so long to arrive at this. The downside, or rather, the upside of this is that I can’t do anything other than read, because typing, moving the mouse pointer via the touchpad and everything else becomes more demanding.
It’s definitely not a substitute for paper, but it’s better than the other options.
What other options, you ask? I found this tool called Readability, which makes reading HTML pages so much easier. I tried converting pdf to HTML, but when you have a combination of text and images and tables, like in many published papers, the conversion is not perfect, and there are quite a few hiccups in reading seamlessly.
I also tried converting .pdf into the Sony Mobipocket format, but again, seamless conversion is a lofty aim, it turns out. The results are hard to read.
So… for now, it’s Ctrl-Alt-leftArrow.
Do you have a better way to read PDF files? Please do share.
I_Am_Back post… and a webapp idea January 3, 2010
Posted by wanderlust in ideas.Tags: google appengine, plagiarism, plagiarism detection, webapp
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I’ve had an extremely nice two weeks, and have come back fully rejuvenated. Not once during the two weeks did I think of what’s on during my quarter. Now I guess I can restart all that.
Now I have an idea for a webapp. Something quite easily implementable on Google Appengine, I guess….
Let’s call it Don’tLiftMyContent!
It’s primarily supposed to be a service that checks if your blog’s or website’s content is being plagiarized elsewhere. Like, you give in your blog’s URL, and it gives you a list of pages that use your images and your text. And for this, it can use existing stuff like Google/Yahoo/Bing for text and TinEye for images. While the web search engines are reasonably good for text, TinEye doesn’t yet have such a comprehensive database of images, and this would probably be the limiting factor of the webapp.
I guess timestamps can be compared in order to eliminate sources your blog has plagiarized/borrowed from
Since this idea occurred to me just a few minutes back, all the existing work I could find are websites which enable teachers to check if their students are plagiarizing. I haven’t yet found a website which does this for blogs, and will be very glad to know if there is.
What say about the idea? Interested? We can code this together, if you want.
Food for thought: how will I know if someone gets the idea from this post of mine and goes on to create this webapp and not give me any credit at all?
Beginning with LaTeX November 29, 2009
Posted by wanderlust in softwares and tools.Tags: LaTeX, LEd, MikTeX
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Using LaTeX for the very first time. I’m finding the LaTeX wikibook rather useful. I’m using LEd and MikTeX. Simple so far. Here goes nothin’.
Creating IPhone Mockups using Adobe Fireworks November 23, 2009
Posted by wanderlust in websites and tips.Tags: adobe, adobe fireworks, fireworks, human computer interaction, prototype, iphone, mockup
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I’ve taken an introductory course in Human-Computer Interaction, and as part of it, I need to create paper prototypes of an IPhone app. We folks considered actually doing it on paper, as our instructor suggested, and decided it’ll be way too much of a pain. We found these rather useful links which told us how to use Adobe Fireworks for creating iPhone mockups.
First on is the link to download a trial version of Adobe Fireworks, or buy it, if you so wish. Here.
Then this toolkit by folks at Blogspark, where every element you need has been redrawn as a vector so that you can edit it to your heart’s content, copy-paste, drag-drop… here.
And finally, this video explaining how to go about making iPhone mockups using the toolkit. Here.
It’s really really easy. Even a total noob like me, who has no idea of what looks good and has no experience of designing goodlooking things on the Net could come up with rather slick-looking iPhone screens. It’s great that there’s a framework like Fireworks which is designed explicitly for web prototyping. Fifteen minutes into the video, and you should be able to figure out most things on your own.
Damn awesome. I’m using Fireworks much more often now.
The Google Earth API November 19, 2009
Posted by wanderlust in APIs, google.Tags: google earth, kml
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I’ve been using it for the past couple of months, for visualizations.
Here, go on and read the documentation. It’s rather well-written.
The short of it: You can access the API using Javascript. But the fun doesn’t begin until you’ve begun with KML.
More coming up. I’ve been working on this quite a bit.
List of things to blog about October 28, 2009
Posted by wanderlust in Uncategorized.Tags: genetic algorithms, google appengine, google earth, identity resolution, machine learning, markov chains, netflix, UCI
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I come across a lot of interesting stuff. Every Day. And I haven’t blogged about ANY of them!
The Distinguished Speaker Series from the Center for Machine Learning at UCI has been really interesting so far. And so has the weekly seminars by the same Center.
I quite enjoyed Prof. Peter Stone’s “Learning and Multiagent Reasoning for Autonomous Agents”. Material related to the talk is available here. I haven’t given robotics a serious thought, though if I get more reasonably into Machine Learning, I should want to try out games, strategies, and all that.
Then there was Prof. Doug Oard who talked about extracting identities from a set of emails. So now you refer to a Judy in your email, or even cutie pie, the software should be able to pick out who you’re talking about, just by being given a set of previous correspondences.I was QUITE interested. It didn’t seem that challenging learning-wise or applying concepts-wise, but I guess the challenge is to figure out how to extract features. And it turns out simple methods are the ones that work best.
There was also Judy Olsen from PARC, who talked about identity resolution on the Net, and how that could be used to obtain biases in Amazon.com reviews. So say X reviews a book by Y. And you find that X and Y are strongly related. You can take that into account while giving weight to reviews. Here, they didn’t use anything more than plain keyword matching on Google search. Just googling for X and Y and determining how much of overlap between the results existed. And the results turned out surprisingly good. I’m wondering about also using sentiment analysis here to determine if the bias would be positive or negative.
The most recent one was Prof. Padhraic Smyth, one of the judges of the Netflix contest talking about the nature of the contest, how it went on, the details in the data, some assumptions….. I came in half an hour late, but still managed to enjoy the rest of the talk.
And the reason I missed half of it? I’m currently a Graduate Student Researcher with Prof. Bill Tomlinson. I’m working on visualizations using Google Earth. My most recent working code will always be posted here. I should aggregate all my knowledge about Google Earth’s API and KML here. Sometime Soon. It’s rather fun.
I’m also taking an AI course this quarter, and my class project has to do with cryptogram solving. The approach I will be using is word-based genetic algorithm. You can check the paper out here [pdf]. I will be uploading the code to Google Appengine once I’m done with it, or atleast gotten started.
And then there’s Probability Models, where I’m supposed to read up on how Markov Chains and the like are used in solving problems. I want to check out how it’s done in text mining. More details forthcoming.
That’s it for now. More coming up, hopefully. I should make it a regular habit to blog here every single day so that I don’t lose what I learn.
Hopeful increase in posting frequency September 27, 2009
Posted by wanderlust in Uncategorized.add a comment
I know no one is subscribed to this space. That’s a major demotivation in posting… especially because my other blogs clock atleast a hundred hits a day. And I’m not a good geek yet… I just take in information.
But now, I’m a graduate student at the Bren School at UCI. Hopefully I’ll regurgitate all that I learn there on this space. It might possibly help me later on.
But the workload doesn’t seem a cakewalk… oh, well, I’ll find time somehow or the other. All that matters is the interest. And who knows, it might turn out productive.
I have lined up a course in Probability Models, one in Human-Computer Interaction, and yet another in Artificial Intelligence. AI seems to be going to be an awesome course… our project is cryptogram solving. Literature survey needs to be done. ASAP. And… I guess that’s going to be work in progress for the rest of the quarter, with implementations on the side.
I’ll also be a Graduate Student Researcher this quarter. There’ll probably be lots of learning on that job. I’ll blog about it as regularly as I can.
So.. hopefully, there’ll be an uptick of posts on this blog. And maybe there’ll be more followers, more networking, more all that that comes with it.
Two problems I want to work on. July 7, 2009
Posted by wanderlust in collaborative filtering, machine learning.Tags: classification
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More on this later. Busy now. If I don’t post on this now, I never will. And… I need some public place where I can keep these links together. I don’t like using del.icio.us, for some reason.
Gender Analysis. June 21, 2009
Posted by wanderlust in machine learning, text mining.Tags: classifier, gender differences, pronouns, writing style
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I didn’t do as much literature survey on this as I’d've wanted, but I came across this paper [pdf]. Word frequencies are different among men and women, apparently. That’s the basis of disambiguation. Women use more pronouns than men do, and the frequency compares with that of fiction, while that of men compares with nonfiction.
So I guess it should work like this: identify genre of the piece, and then identify gender.
What say?
