Forum

Data format for Sequential Patterns with time-series (2 replies)

YougyZ — Wed, 16 May 2012 23:18:02 -0400

Hello all,

I am newbie in the sequential patterns mining. Right now, i am doing my internship and i will implement this method.

I need help for the datasets that will fit for the sequential pattern with time-series.

I have prepared an example of datasets like below :

Time M_T_ambiante DeltaT M_T_Ext M_Rayonnement
20/06/2011 00:00 Medium Normal Medium Low
20/06/2011 00:05 Medium Normal Medium Low
20/06/2011 00:10 Medium Normal Medium Low
20/06/2011 00:15 Medium Normal Medium Low
20/06/2011 00:20 Medium Normal Medium Low
20/06/2011 00:25 Medium Normal Medium Low
20/06/2011 00:30 Medium Normal Medium Low

Is this datasets already can be used with sequential patterns like GSP or else?

Thanks before your help.

Regards,
Yogi

SPAM vs PrefixSpan (5 replies)

Dvijesh88 — Wed, 02 May 2012 03:16:23 -0400

I just want to know which algorithm better? please tell me with all points.
where to use these algorithms?

Ph.D project in data mining (4 replies)

Tenjiku — Tue, 08 May 2012 21:45:47 -0400

Hi. I'm a student. I want to do a Ph.D. in data mining but i don't know which topic is interesting. Could you recommend me research topics about data mining? I have heard of doing decision tree but i think that it is too simple. Could you give me a good research topics for doing my phd in data mining????

Big Data, the next Big bubble? (no replies)

webmasterphilfv — Tue, 24 Apr 2012 10:54:17 -0400

Hello,

Many people in the data mining industry are talking about a new buzzword "Big Data", which is just a new word to talk about how to address the scalability problem of data mining algorithms for handling huge amount of data, and their storage.

Is this new buzzword a big bubble? That is what this person seems to think:

[mlcwideangle.exbdblogs.com]

Personally, I tend to agree that large-scale data mining is appropriate only for big businesses. But as researchers, we should still aim at developing data mining algorithms with good scalability.

"Big Data" is probably over-hyped right now... I read some data mining websites like KDNuggets and more than half of the news has the word "Big Data" in it. I mean, scalability and data integration has always been an important aspect of data mining. But we should not only focus on this aspect.

Phil

PAKDD 2012 Data Mining Competition announced! (1 reply)

webmasterphilfv — Wed, 18 Apr 2012 18:35:09 -0400

The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is pleased to organize a data mining competition. The competition is divided into two categories:

1. Open category (open to both academia, industry and students). The tasks for this category involve predicting customer churn and win-back for a large telecommunication company. The prizes for the competition are sponsored by the Faculty of Computing and Informatics, Multimedia University.

2. Student category (open to only students enrolled at institutions of higher learning). The task for this category involves discovering the correlation between the number of job applications and Malaysia's economic indicators. The prizes for the student category is sponsored by SAS Malaysia.

The deadline for submitting the final entries is May 13, 2012. More details are available on the competition web site at http://fit.mmu.edu.my/pakdd2012/dmcomp.html.
The competition web site is also accessible via the PAKDD 2012 web site at pakdd2012.pakdd.org

VLDB/Cloud-I 2012 - 1st International Workshop on Cloud Intelligence (Cloud-I 2012) (no replies)

webmasterphilfv — Mon, 16 Apr 2012 08:32:33 -0400

***************************************************************
1st International Workshop on Cloud Intelligence (Cloud-I 2012)
***************************************************************
In conjunction with VLDB 2012, Istanbul, Turkey, August 31, 2012

[eric.univ-lyon2.fr]
Contact email: cloud-i@eric.univ-lyon2.fr

*** NEW ***

The best accepted papers will be invited to submit extended versions to a special issue of the Information Systems journal.

***************
CALL FOR PAPERS
***************

With the increasing success of cloud computing, cloud business intelligence "as a service" offerings have sparkled widely, both from cloud start-ups and major BI industry vendors. Beyond porting BI features into the cloud, which already implies numerous issues (e.g., BigData/NoSQL database modeling and storage, data localization, security and privacy, performance, cost and usage models...), this trend also poses new, broader challenges for making data analytics available to small and middle-size enterprises (SMEs), non-governmental organizations, web communities (e.g., supported by social networks), and even the average citizen; this vision presumably requiring a mixture of both private and open data.

The aim of the Cloud-I workshop is to become an interdisciplinary, regular exchange forum for researchers, industry and practitioners, as well as all potential users of Cloud Intelligence. The submission of research, industrial, position, visionary and student papers are encouraged to fuel up the discussion.

The 1st International Workshop on Cloud Intelligence (Cloud-I 2012) will be collocated with the 38th International Conference on Very Large Databases (VLDB 2012).

The best accepted papers will be invited to submit extended versions to a special issue of the Information Systems journal.

* Topics of interest

The topics of the Cloud-I workshop include, but are not limited to, the following list.
- Accessibility of Cloud Intelligence
- Analytics for complex data
- Analytics for social networks
- Analytics for temporal, spatial, spatio-temporal and mobile data
- Benchmarking Cloud Intelligence applications
- Cloud data warehouse design and architectures
- Cloud infrastructure for analytics applications
- Cloud Intelligence on linked data
- Collaborative Cloud Intelligence
- Cooperative Cloud Intelligence
- Crowd intelligence
- Data analytics as a service
- Data mining over the cloud
- Economic/payment models for cloud intelligence
- Extracting, Transforming and Loading data over the cloud
- Human-Computer interaction for Cloud Intelligence
- Massive data analytics: algorithms, techniques and systems
- OLAP over the cloud
- Open and private data cross-integration
- Personal intelligence
- Privacy and security in Cloud Intelligence
- Real-time/right-time and event-based analytics, performance issues
- Reliability and fault tolerance in Cloud Intelligence
- Scalability and parallelization for Cloud Intelligence: MapReduce and beyond
- Semantic Web intelligence
- Sharing and reusing Cloud Intelligence results

* Important dates

- Paper submission deadline: May 1, 2012
- Notification of acceptance: June 5, 2012
- Camera ready paper submission: June 12, 2012
- Workshop date: August 31, 2012

* Submission guidelines

Papers must be submitted electronically as PDF files following the VLDB camera-ready format.
[www.vldb2012.org]

Papers must not to exceed 8 pages in length and must be submitted electronically on the workshop’s web page.
[eric.univ-lyon2.fr]

* Workshop chairs

- Jérôme Darmont, Université de Lyon, France
- Torben Bach Pedersen, Aalborg University, Denmark

* Program committee

- Alberto Abello, Universitat Politècnica de Catalunya, Spain
- Sihem Amer-Yahia, Qatar Computing Research Institute, Qatar
- Sandro Bimonte, CEMAGREF Clermont-Ferrand, France
- François Briant, IBM France
- Laurent d'Orazio, Université Clermont-Ferrand II, France
- Amr El Abbadi, University of California, Santa Barbara, USA
- Matteo Golfarelli, University of Bologna, Italy
- Le Gruenwald, University of Oklahoma, USA
- Anne Laurent, Université Montpellier 2, France
- Daniel Lemire, Université du Québec à Montréal, Canada
- Ioana Manolescu, INRIA Saclay, France
- Morten Middelfart, TARGIT & illo, Denmark
- Jose-Norberto Mazon, University of Alicante, Spain
- Mathias Paulin, We Are Cloud, France
- Stefano Rizzi, University of Bologna, Italy
- Juan Trujillo, University of Alicante, Spain
- Panos Vassiliadis, University of Ioannina, Greece
- Gottfried Vossen, Universität Münster, Germany

Call for Springer Book Chapters: Security and Privacy preserving in Social Networks (extended chapter description proposal deadline) (no replies)

webmasterphilfv — Mon, 16 Apr 2012 08:30:37 -0400

##########################################################################################################################
Book on Security and Privacy preserving in Social Networks
To be published by Springer Verlag (Lecture Notes in Social Networks)
[dbconf.u-bourgogne.fr]

Description and Objectives
---------------------------

Online social networks provide users, within their platforms, powerful ways to interact with other users through different forms and modalities.
Consequently, each user can search and check the profiles of her social network members (for various reasons), exchange messages with some of them, publish some photos, and post comments on shared photos, etc.
Although such tools are attracting continuously more and more users, several security and privacy problems related to their usage are emerging.
For instance, how to provide users with an easy way to protect their shared data? How to protect a data repository (e.g., photo album) while several related information about the same content is already published (by some user friends) on the same or other blog/wiki/social network? How to define publication strategies? etc.

The general aim of this book is to assess the current approaches and technologies, as well as to outline the major challenges and future perspectives, related to the security and privacy protection of social networks.
It provides an overview of the state of the art, latest techniques, studies, and approaches as well as future directions in this field, by including a wide range of interdisciplinary contributions from various research groups.

The primary target audience for the book includes researchers, scholars, postgraduate students and developers who are interested in social network security and protection.

Topics
-------

Below is a non exhaustive list of topics to be addressed by the chapters:

- Social network description and representation
- Trust and privacy management
- Risks and threats of social networking
- Trace analysis on social networks
- User profiling and related risks
- Ethical conflicts in social networks as well as the moral implications
- Relationship management and discovery
- Anonymity preserving
- Social terrorism
- Social network-based access control
- Abnormal activities on social networks

Paper Submission
----------------
Authors are kindly invited first to send (before April 25, 2012) a brief email to the editors in which they provide a description of the chapter to be submitted.
Full chapters (not exceeding 50 pages) must be uploaded before June 15th 2012 at:

[dbconf.u-bourgogne.fr]

All submitted chapters will be reviewed by at least two reviewers.

Important Dates
----------------

- Deadline for brief chapter description proposal: April 25th, 2012 (extended)
- Deadline for chapter submission: June 15th, 2012
- Notification of acceptance/rejection/revision of chapters: August 15th, 2012
- Deadline for submission of final chapters: September 15th, 2012
- Publication of the book: End of 2012

Editors
--------------
Richard Chbeir, Bourgogne University, France (richard.chbeir@u-bourgogne.fr)
Béchara Al Bouna, Qatar university, Qatar (bechara.albouna@gmail.com)

International Editorial Board Members
-------------------------------
(see the web site for the full list)

SPMF 0.81 is released! - Improved SPAM implementation (2 replies)

webmasterphilfv — Thu, 19 Apr 2012 00:38:47 -0400

Hello everyone,

This is just to let you know that I have published a new version of SPMF (0.81).

In this version, I have improved the SPAM implementation.

Before my SPAM implementation used a fixed number of bits for each sequence. I have modified the code so that it now uses a variable number of bits for each sequence. This is the main difference.

The implementation is therefore more memory efficient and can run on larger database with longer sequences. It is also faster on some datasets because it uses less bits.

Philippe

[JAVA] [C#] how to calculate the maximum memory usage of a data mining algorithm (5 replies)

webmasterphilfv — Wed, 09 May 2012 07:55:01 -0400

Hello,

Today, I received a question today about how to compute the maximum memory of a data mining algorithm like FPGrowth in Java.

It is very simple. I do like that.

I add a variable :

double maxMemory = 0;

Then I copy and paste this method:

private void checkMemory() {
        double currentMemory = ((double) ((double) (Runtime.getRuntime()
                .totalMemory() / 1024) / 1024))
                - ((double) ((double) (Runtime.getRuntime().freeMemory() / 1024) / 1024));
        if (currentMemory > maxMemory) {
            maxMemory = currentMemory;
        }
    }

Then, I call the method

checkMemory()

from where I want to check the memory.

Finally, I print the result:

System.out.println("memory : " + maxMemory);

Philippe

Six computer science courses for free online. Has to register before April 16th 2012 at Udacity... (no replies)

webmasterphilfv — Fri, 13 Apr 2012 00:25:45 -0400

Hello everyone,

I found an interesting website called Udacity.com.

It offers some free computer science courses that you can take online and that start April 16. They take 6 weeks and there is some homeworks and exam. The courses are:
- CS 101 : How to build a search engine (for beginner, starts April 16 - 7 weeks)
- CS 212 : Design of computer programs (starts April 16 by Peter Norvig a famous researcher working at Google).
- CS 253 : Web Application Engineering
- CS 262 : Programming languages
- CS 373 : Programming a robotic car
- CS 387 : Applied cryptography.

And these courses are completely free!

I have registered to applied cryptography to see how it works.

Best,
Philippe

SPMF 0.80 is released! (2 replies)

webmasterphilfv — Mon, 09 Apr 2012 09:07:22 -0400

Hello everyone,

I have released a new version of the SPMF data mining software.

This new version provides the following main changes:
- I have improved the user interface thanks to N. Kali !
- I have cleaned the code of several files to remove some unused methods.
- I have changed the license. The source code is now under the GNU GPL v3 open-source license. This will help to make the software more open and reusable by other open-source projects.
- I have added a list of contributors on the website to thanks people who have reported bugs and gave me suggestions to improve the software.
- I have added a link to the forum on the website in the left menu.

Besides, I'm looking for contributors who would like to participate by implementing algorithms. If some of you have source code for algorithms that I don't have and would like to contribute to the project, I could add your source code to SPMF and put your name in the contributor list on the website. But of course, before adding any other algorithms, I will check the source code quality.

The user interface in this version of SPMF:

Have a good week-end,

Philippe

2012 [French] - call for papers (2 replies)

webmasterphilfv — Mon, 09 Apr 2012 09:05:40 -0400

5èmes Journées thématiques
"Apprentissage Artificiel & Fouille de Données"
AAFD'12
28 et 29 juin 2012
Université Paris 13, Institut Galilée
________________________________________

Le LIPN et le L2TI, avec l'appui du groupe Data Mining et Apprentissage de la SFdS (Société Française de Statistique), organisent les 28 et 29 juin 2012, la cinquième édition du colloque AAFD "Apprentissage Artificiel & Fouille de Données" à l'Institut Galilée. Cette manifestation réunit plus d'une centaine de chercheurs et d'industriels travaillant dans ce domaine. Le colloque AAFD a pour objectif premier de permettre aux intéressés de mieux découvrir ce domaine et avoir une vision synthétique sur l'état de l'art, et aux spécialistes de nouer des contacts avec d'autres équipes de recherche. Le thème central de cette manifestation est l'utilisation des techniques d'apprentissage artificiel pour l'analyse et l'exploration de données afin d'en comprendre le sens, de déceler des relations entre des événements, d'en déduire des modèles de comportement.
L'objectif de ces journées est de faire le point sur l'état de l'art des techniques et des applications utilisant l'apprentissage artificiel dans le domaine de la fouille de données. Elles constitueront une opportunité de rencontres entre chercheurs et industriels oeuvrant dans le domaine de l'extraction de connaissances et l'apprentissage artificiel à partir de données.

>>> Inscription sans frais mais obligatoire, déjeuner offert sur place <<<

Programme complet [www-lipn.univ-paris13.fr]

Comité scientifique :
Y. Bennani (LIPN-UP13)
E. Viennet (L2TI-UP13)

Top data mining mistakes (no replies)

webmasterphilfv — Fri, 06 Apr 2012 08:26:23 -0400

Hello,

I have found this great article describing some "top data mining mistakes".

[www.sas.com]

Philippe

Applications of sequential pattern mining (1 reply)

webmasterphilfv — Wed, 04 Apr 2012 12:47:29 -0400

Hello,

Today I received a question by e-mail : "What are the applications of sequential pattern mining?"

Here is my answer. Feel free to add some other applications by replying.

Mining transactional data

It is possible to mine sequential patterns in sequences of transactions from a store. In this case, each sequence represents the transactions from a customer at the store. From this, a sequential pattern mining algorithm could find patterns common to several customers. For example, 30 % of the customers who buy beer and pizza, buy milk after. This could be used for taking marketing decisions or for product recommentation on a web store.

Mining web logs
Sequential pattern mining can be done on web logs. In this case the sequences could be sequences of webpages visited by users on a website. From this data, a sequential pattern mining algorithm could use sequential pattern mining to discover sequences of web pages that are often visited by users . The website could then use these patterns to generate suggestions to the user such as recommended links.

Mining medical records or health data
Sequential pattern mining algorithsm could be used to find patterns in medical records. For example, let's say that each sequence is the medical record of a person in a hospital. Patterns could be found such as that people who took the medicine A and the medicine B, and then the medicine C, will have a heart attack for example.

Mining educational data
Sequential pattern mining can be used to find patterns in educational data. For example, consider that each sequence of a sequence database is the courses that a student took at university. It would be possible to discover patterns such as people who took course A and B will always take the course C.

Mining stock market data
Sequential pattern mining could be applied to sequence of events on the stock market.

Software engineering
Sequential pattern mining could be applied in software engineering to find patterns in source code.

How to get live social network data for data mining (1 reply)

webmasterphilfv — Sat, 31 Mar 2012 07:32:23 -0400

Hello everyone,

For those of you interested in social network mining and social network analysis, I have found two websites for getting live social network data from social networks websites like Twitter, Facebook, Hulu, Digg, Myspace, Google+, Youtube. I want to share this with you:

GNIP

[gnip.com]
This website offers live social network data for many networks like Twitter, Facebook,Hulu, Digg, Myspace, Google+, Youtube;...
It is a commercial service. To use the service, we need to pay a few thousand dollars per month. However, by calling the customer service, it is possible to get a free trial for a few weeks. This could be enough for gathering enough data for data mining.

DATASIFT

[datasift.com]
This website offers live data from Twitter, IMDB, Digg, Amazon, Flickr, Myspace, reddit, youtube ....
When registering, 10 $ of free credits are given for testing.
For example, it costs 0.1 $ for 1000 tweets. So for 10 $, you can get 100 000 tweets for free. It is maybe possible to get more free credits by calling the customer service.

Also note that these two services allow to specify constraints on the data that you want to receive. For example, you can say that you want only the Tweets that are containing the word "camera".

You can also access the data from Java code to manipulate the data and perform some data mining.

I think that it is very interesting and it can provide many possibilities for data mining projects about social networks.

Philippe

Most popular programming langages (4 replies)

webmasterphilfv — Wed, 04 Apr 2012 12:40:29 -0400

An interesting article about the most popular programming langages right now (2012):

[www.tiobe.com]

Here is the top 10:
1- Java
2- C
3- C#
4- C++
5- Objective C
6- PHP
7- VB
8- Javascript
9- Python
10- Perl

It is not directly related to data mining. But I thought that it is an interesting article to share!

Philippe

Oracle Data Mining (no replies)

webmasterphilfv — Wed, 28 Mar 2012 17:51:29 -0400

Hello everyone,

I was looking at the Oracle Data Mining page and I just want to share my thoughts about it.

The webpage: [www.oracle.com]

The webpage list the data mining tasks/algorithms that Oracle has implemented:

- Apriori
- SVM
- Matrix factorization
- KMeans
- Orthogonal partitional clustering
- Min. Description length
- Regression
- Decision trees

My comments:
- this list does not contains many algorithms.
- some of these algorithms are outdated. Apriori could have been replaced by FPGrowth for example
- there is some nice pictures on that page that explain visually what these data mining tasks are
- if you click on the algorithms on the page there is some explanation about how the algorithms works and they also show the user interface. For example, when I click on "associations" i get that page: [docs.oracle.com] which show the user interface for mining associations.

Is there anyone who study the paper (no replies)

leitang — Mon, 26 Mar 2012 12:03:41 -0400

I am now studying the paper which can been download from the link : [www.cse.ust.hk]

I hava implemented the InfoMiner algorithm, And I want apply it into classfication. But the period length is hard to decide.Is there someone who studied it before.I want your help.
Thank you.

Elsevier & open-access articles. (6 replies)

webmasterphilfv — Fri, 23 Mar 2012 21:48:11 -0400

I received a newsletter from the publisher Elsevier today.

In the e-mail there is a link to an article on their website: "Open Access The choice is yours - Open Access options at Elsevier".

Basically, when i click on the subpage "information" it says that when you publish an article at Elsevier, you can pay 3000 $ US so that it becomes available for free to everyone.

So expensive!

For those of you who don't know, there is more than 8000 researchers that have started to boycott Elsevier journals a few days ago:

[www.ibtimes.com]
[the-scientist.com]

Analysis of mining Frequent sequential pattern algorithm's (43 replies)

vivek basati — Sun, 22 Apr 2012 10:10:58 -0400

hi everyone.

In frequent pattern mining algorithms like prefix-span or SPAM or

among any other algorithms which one would be efficient??

If you cant say directly, can you clarify me which one would be efficient

considering criteria's like time,memory,no. of counts etc...??

Ill be glad if anyone help me in this analysis.:)

Doubts in SPAM algorithm (2 replies)

vivek basati — Thu, 22 Mar 2012 12:27:35 -0400

hello sir,

i have problem in executing SPAM algorithm in SPMF FRAMEWORK.

Electronic Brain (no replies)

omari.abdallah — Tue, 20 Mar 2012 19:35:34 -0400

Dear searchers, students

I have the big pleasure and the big honor to inform you about my new book "Electronic Brain", that contains the result of 12 years of my researches in the neural network field, I present in this book a new model of neural network named El-Dorra, and I include a new learning methodology as the separated learning, continued learning and artificial forget in order to obtain the Electronic Brain.

This technology erases the problems of ANN such as: Local solutions, long time learning, bad precision, random modeling (Nbr hidden layer) ,..
This new technology was supported trough 12 years (1998-2010) by many international conferences as:
CICMA'04 Australia, ICBP'04 Sweden, ICIMA'04 China, ICINCO ANNs'04 Portugal, IKS'04 Turkey, ISNB'04 Holland, Bioinformatics'04 Sweden, MML'04 Italy, SCT'04 USA, CITSA'04 USA, ICDL'04, BICS'04 UK, Wesas'05 Portugal, NNSC'05 Poland, Isf'05 Texas, ICIT'05 Jordan, ISC 2005 Berlin Germany, Wseas'09 Cambridge, FICNPSC 2010 Atlanta Georgia USA, ICADIWT 2010 Turkey, ICAI'10 Las Vegas, Nevada USA, ICCA ‘10 India, ICCNSE 2010 Japan, ICICCA2010 India, …. And others

You can found the book Electronic brain (Available now!):
[www.futurespublications.co.uk]
Or, on Amazon (not available yet):
[www.amazon.co.uk]
• ISBN-13: 978-1871131215

For more information or purchase you can contact my agent in UK Mr Roger Loughney : roger@tandempress.com, or the publisher : [www.futurespublications.co.uk]

Nb: in order to save my rights, I never publish my work in any journal, even it accepted by many height level International Conferences, so you can not found this technology out of this book.

Best regards

OMARI Abdallah
International searcher on neural networks modeling & learning methodology
omariabdallah@maktoob.com , omariabdellah@yahoo.fr

Survey: what is your favorite data mining algorithm? (10 replies)

webmasterphilfv — Fri, 23 Mar 2012 00:59:13 -0400

Hello everyone,

I would like to ask you: What is your favorite data mining algorithm?

Personally, I have a few favorites:
- the PrefixSpan algorithm for sequential pattern mining. This algorithm is relatively simple. There is also some good ideas in its design such as pseudo-projection and pattern-growth that makes it very efficient.
- the Apriori algorithm for frequent itemset mining. It is not very efficient. But it is simple and it has inspired hundreds of researchers afterward and many algorithms are still based on it.
- the K-Nearest Neighboor algorithm. This algorithm can be implemented using a KD-Tree data structure. I think that the KD-Tree data structure is very interesting because it allows to calculate the nearest neighboor very efficiently.

What are your favorite data mining algorithms?

Phil

How to use IBM_Quest_data_generator to generate web logs (4 replies)

Yuan — Sat, 07 Apr 2012 00:20:00 -0400

Hello!
I just learned to use IBM_Quest_data_generator to generator sequence patterns like this:
6 1 9033 3 1845 7713 8778 3 1285 1705 7890 3 4049 6908 7443 2 765 1739 2 3627 9693
1 2 269 4701
......
.....
but what I really want is web logs like:
6 9033 1845 7713 8778 1285 1705
2 269 4701
...
could you tell me how to generator web logs?

Data Mining for game design (no replies)

webmasterphilfv — Fri, 16 Mar 2012 23:51:21 -0400

Hello everyone,

Here is an interesting article about how to use data mining in game design:

[www.gamasutra.com]

The authors claims that data mining can help MMOG design by:
1. To balance the economy
2. To catch cheaters
3. To cut production costs
4. To increase customer renewal

Besides that, I found that some people provides datasets from the StarCraft game:

[eis.ucsc.edu]

But I did not find datasets for other games.

Best,

Philippe

What is data mining? A picture to explain it! (no replies)

webmasterphilfv — Fri, 16 Mar 2012 21:56:29 -0400

Hello,

For those who have trouble to see the relationship between the various data mining techniques, there is a visual classification of data mining techniques on this website (http://chem-eng.utoronto.ca/~datamining/dmc/data_mining_map.htm ). Of course, it is not perfect. But it is interesting.

Note that on the website, you can click on the pictures to get a description of the techniques.

Phil

An interesting article about why sharing algorithms as open source... (6 replies)

webmasterphilfv — Mon, 19 Mar 2012 11:37:06 -0400

Hello,

I want to share an interesting article:

"The Need for Open Source Software in Machine Learning"
[jmlr.csail.mit.edu]

It is about why researchers should share the source code of their algorithms with other researchers.

Personally, I agree with this article. Too many researchers don't want to share their source code or even their implementations or datasets.

Philippe

gSPAN & graph mining algorithms source code (1 reply)

Jeff — Mon, 12 Mar 2012 15:12:14 -0400

Hello,

Does anyone has Java source code for graph mining algorithms such as gSpan? I'm looking for source code and also some datasets.

I want to perform some data mining experiment on social networks (twitter, dblp etc.).

Also, someone know where i can download the last version of the dblp dataset?

Thanks for your help!

Jeff