Develop Reference

Android/PC GIS library wanted

I have a task to develop an application with some GIS-functions: rendering of the previously downloaded map (with different layers and in different modes), programmatic assignment of markers and tracks, a path searching. It must be implemented under Android and PC (Win) and must be able to work offline. So I need a library which provides capabilities specified above and satisfies some additional conditions.
If possible, cross-platform (i.e. with a common core and with a different GUI under PC/Android).
Free for commercial use or without requirement of any user license in addition to the developer license.
Open-source is preferable (GPL/LGPL/MIT-like is ideal).
Java API is preferable.
After some days of googling I came to the conclusion that such a thing didn’t exist at all. There are many open-source GIS products in Java but no one of them is Android-compatible. So my goal is to find a library with an ability to render some map region into the picture and an ability to tell me coordinates by the specified picture pixel. At least I can use different PC-only and Android-only products to develop two different applications parallely.
Please, can anybody suggest me anything applicable for my task. Maybe somebody has some experience in this area. Any information is appreciated.
Thanks a lot.

Whilst not a full GIS library I have used JTS to write code on both PC and android.
The Website is http://www.vividsolutions.com/jts/JTSHome.htm
Whilst the documentation is a little on the light side I have found that it isn't to hard to implement. Using standard drawing functions I have been able to set up some basic GIS applications and mapping functions.

How page ranks are calculated in real time

I have read the explanation in http://en.wikipedia.org/wiki/PageRank and i understand that the page rank is calculated by incoming links and out going links.
I have a crawler while crawls a webpage and store in db i need an page-rank algorithm.
I have a db with following values
Title
url
content_html
outgoing_links(external domain)
internal_links(the links with same domain of the url)
can u please explain do i need any other value to compute the page rank and. please explain how to compute it using java

PageRank is, at its heart, a linear algebra eigenvalue problem:
http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf
If you don't know linear algebra or eigenvalue problems, or aren't willing to read this paper, it's unlikely that you'll be able to tackle this problem. As Einstein said, "Make the problem as simple as possible, but no simpler..."
The paper's title is old; it refers to Google's market cap circa 2004. It's up to $211B this morning.
The technology hasn't stood still in all that time. Google continues to tweak the algorithm in proprietary ways. But this paper explains the heart of it.

You have a few options. If you want to do it all yourself then duffymo's solution is perfect but if you want to use existing libraries I would suggest something similar to Jung for graphs.
I'm not sure if your familiar with graphs but they can be used to store the structure of the links and pagerank is often included in most libraries. Depending on how you want to do it, a good in memory solution is Jung but if you need persistent database storage than loading your data into Neo4J would work(you would have to install gremlin to do the pagerank).
The above are Java solutions but if you want to do it yourself(and like me don't like dry research papers) then I would highly suggest the book programming collective intelligence. They go through(chapter 4? I think) creating a search engine from scratch that includes pagerank and neural networks to monitor clicks. The only problem, based on your requirements above, is the book is written in python but you can easily apply the logic to java. If you know a bit of python already then you can even download the books source code for free and check out the software(but there is no explanation on the math behind the code in the source code).
Hope that helps

Machine learning challenge: diagnosing program in java/groovy (datamining, machine learning)

I'm planning to develop program in Java which will provide diagnosis. The data set is divided into two parts one for training and the other for testing. My program should learn to classify from the training data (BTW which contain answer for 30 questions each in new column, each record in new line the last column will be diagnosis 0 or 1, in the testing part of data diagnosis column will be empty - data set contain about 1000 records) and then make predictions in testing part of data :/
I've never done anything similar so I'll appreciate any advice or information about solution to similar problem.
I was thinking about Java Machine Learning Library or Java Data Mining Package but I'm not sure if it's right direction... ? and I'm still not sure how to tackle this challenge...
Please advise.
All the best!

I strongly recommend you use Weka for your task
Its a collection of machine learning algorithms with a user friendly front-end which facilitates a lot of different kinds of feature and model selection strategies
You can do a lot of really complicated stuff using this without really having to do any coding or math
The makers have also published a pretty good textbook that explains the practical aspects of data mining
Once you get the hang of it, you could use its API to integrate any of its classifiers into your own java programs

Hi As Gann Bierner said, this is a classification problem. The best classification algorithm for your needs I know of is, Ross Quinlan algorithm. It's conceptually very easy to understand.
For off-the-shelf implementations of the classification algorithms, the best bet is Weka. http://www.cs.waikato.ac.nz/ml/weka/. I have studied Weka but not used, as I discovered it a little too late.
I used a much simpler implementation called JadTi. It works pretty good for smaller data sets such as yours. I have used it quite a bit, so can confidently tell so. JadTi can be found at:
http://www.run.montefiore.ulg.ac.be/~francois/software/jaDTi/
Having said all that, your challenge will be building a usable interface over web. To do so, the dataset will be of limited use. The data set basically works on the premise that you have the training set already, and you feed the new test dataset in one step, and you get the answer(s) immediately.
But my application, probably yours also, was a step by step user discovery, with features to go back and forth on the decision tree nodes.
To build such an application, I created a PMML document from my training set, and built a Java Engine that traverses each node of the tree asking the user to give an input (text/radio/list) and use the values as inputs to the next possible node predicate.
The PMML standard can be found here: http://www.dmg.org/ Here you need the TreeModel only. NetBeans XML Plugin is a good schema-aware editor for PMML authoring. Altova XML can do a better job, but costs $$.
It is also possible to use an RDBMS to store your dataset and create the PMML automagically! I have not tried that.
Good luck with your project, please feel free to let me know if you need further inputs.

There are various algorithms that fall into the category of "machine learning", and which is right for your situation depends on the type of data you're dealing with.
If your data essentially consists of mappings of a set of questions to a set of diagnoses each of which can be yes/no, then I think methods that could potentially work include neural networks and methods for automatically building a decision tree based on the test data.
I'd have a look at some of the standard texts such as Russel & Norvig ("Artificial Intelligence: A Modern Approach") and other introductions to AI/machine learning and see if you can easily adapt the algorithms they mention to your particular data. See also O'Reilly, "Programming Collective Intelligence" for some sample Python code of one or two algorithms that might be adaptable to your case.
If you can read Spanish, the Mexican publishing house Alfaomega have also published various good AI-related introductions in recent years.

This is a classification problem, not really data mining. The general approach is to extract features from each data instance and let the classification algorithm learn a model from the features and the outcome (which for you is 0 or 1). Presumably each of your 30 questions would be its own feature.
There are many classification techniques you can use. Support vector machines is popular as is maximum entropy. I haven't used the Java Machine Learning library, but at a glance I don't see either of these. The OpenNLP project has a maximum entropy implementation. LibSVM has a support vector machine implementation. You'll almost certainly have to modify your data to something that the library can understand.
Good luck!
Update: I agree with the other commenter that Russel and Norvig is a great AI book which discusses some of this. Bishop's "Pattern Recognition and Machine Learning" discusses classification issues in depth if you're interested in the down and dirty details.

Your task is classical for neural networks, which are intended first of all to solve exactly classification tasks. Neural network has rather simple realization in any language, and it is the "mainstream" of "machine learning", closer to AI than anything other.
You just implement (or get existing implementation) standart neural network, for example multilayered network with learning by error back propagation, and give it learning examples in cycle. After some time of such learning you will get it working on real examples.
You can read more about neural networks starting from here:
http://en.wikipedia.org/wiki/Neural_network
http://en.wikipedia.org/wiki/Artificial_neural_network
Also you can get links to many ready implementations here:
http://en.wikipedia.org/wiki/Neural_network_software

Graph Control in Java/Netbeans? Does it exist?

Is it possible that anyone has a link to a graph class/library that I can use to produce a graph in Java?
Thanks for any help!

My top choice would be JGraph as others have suggested; I am using JGraph5 because it is better documented than the newer alternative, JGraphX. EDIT: JGraphX turns out to be the far superior version, despite the lack of documentation. It's not that hard to figure out.
JGraph
Demonstration app
Feature list
Licensing agreement
Other alternatives I've researched:
JGraphT
"JGraphT is a free Java graph library that provides mathematical graph-theory objects and algorithms...complete source code included, under the terms of the GNU Lesser General Public License." (http://jgrapht.sourceforge.net/)
Main project repository
Example visualizations
JUNG - Java Universal Network/Graph Framework
Main project repository
yEd Graph Editor
Implementation of yFiles library
Demonstration Java applet
About yEd
Saves graphs in GraphML format

I used JGraph as a visualizer for networks of nodes/topologies at my previous job, it's not half bad once you get past the architecture (it's a big state machine if I recall correctly).

Visual graph: JFreeChart
You may also wish to consider the Google Charts API, if you can make web service requests.

A really good alternative is to used the Google Charts API. Platform independent, easy to use, and fast processing (done on Google Server side)

graphviz would be my choice. It's not Java, but still terrific and easy to use.
There is a Java component that works with dot to generate graphs. I've used it - very nice, indeed.

I would recommend JGraphT. I used it to create multi-leveled graphs in my dissertation and as the base of a GPS Routing Software, understanding what is going on I found a bit of a mind bender, but once looking at how the algorithms package works I found it quite easy to implement A*/D* heuristic algorithms. For working out the distance between nodes on the graph I'd also recommend looking at the Haversine function, if that's your thing.

Providing a common interface to SVN and CVS

SVN and CVS are two very different systems that aim to address the same basic issue - source control.
They both work in distinct ways, so it's probably difficult to deal with them exactly the same.
What I'm wondering is, would it be conceivable to develop a programming library or API that exposes the same interface, but under the hood, can be set up to work with either an SVN or CVS repository?
I'm aiming to develop such a library in either .NET or Java (most likely .NET), but I wanted to get some thoughts on how feasible this would be, and if there's a better way to approach the problem.
The context of this is: I'm building a web-based service that will involve source control hosting, and I want to support both SVN and CVS so as to serve the largest amount of developers possible.

Personally I would ignore CVS for a new product. My feeling would be that the enormous extra effort to coerce it into looking like SVN would be better spent on other other stuff. I don't know your market, so I might be wrong, but that's got to be worth thinking about.

The MSSCCI API does something very similar:
http://alinconstantin.homeip.net/webdocs/scc/msscci.htm
The MSSCCI tries to make all source controls look the same from the perspective of the IDE.

viewvc lets you browse svn and cvs repositories. maybe there is an existing product which will already do what you want?