Distributed Data Mining - Science topic

I think that Generative Adversarial Networks can be used as Data Farming Means. What do you know about such an approach? Can you give another example of means for Data Farming?

Hello everyone,

My issue is about a water distribution system that I am working on a zone of the system where does not exist any plan for the place of pipes. However, we have the place of actuators like different types of valves, pressure relief valves, pressure meters, flow meters and tanks. Also, we have the place of demands where suffer from pressure loss. Now the question is how we can do pressure management using actuators to maximize water pressure for all demands of the zone based on the previous recorded data while we are going to minimize water loss as well as pipes damaging. Please let me know if you have any idea or you know any suitable paper for this issue.

Thanks.

I need to do some comparison with other methods for a new rule of combination under Dempster-Shafer theory. I would like to use the same data used in ‘Combining Multiple Hypotheses for Identifying Human Activities’ by Young-Woo Seo and Katia Sycara. Unfortunately, those data are no longer available at http://www.cs.utexas.edu/users/sherstov/pdmc/ .  This data set was originally released to a Physiological Data Modeling Contest (PDMC) at the site cited above.  Is there someone that can provide me the data or could reference a site where I can get it?

Are you aware of any simulator allowing distributed data mining? I would like find an IoT-based dataset and a simulator allowing me to perform distributed data mining

I have a sort of data in which the change in the weight of materials is recorded during the time. Unfortunately because of special condition I cannot record the weight in the first 75 seconds.

- Is there any way to predict the initial missed data (I mean the change in the weight in the first 75 seconds)?

- How can I find the equation of the curve that fit the data points?

Any solution with MATLAB, SPSS, and Excel softwares is appreciated.

Could you please share some current research trends/topics/techniques in Data Mining and Knowledge Discovery?

Actually I want to implement gauss Seidel method to find out the solution of linear equation system of sparse matrices but now i stuck with the dependency in every iteration and not getting any solution.. please provide some resource so that I could implement it...

Any researcher

Hi all,

I'm currently working with hadoop using Hadoop 2.3.2 Hortonworks sandbox that runs on VMware.  I wish to load a dataset by following the "hello world" tutorial as provided by Hortonworks webpage. I followed exactly the steps in that tutorial. As said in that tutorial, to load a dataset, I need to create a temporary data directory by clicking on the new directory button. However, the new directory button is disabled in the admin ambary dashboard. Does anyone here has any suggestion or recommendation on any other better hadoop installer which is more easier?

I was trying to implement the USD algorithm (Paper Tile: Discretization oriented to Decision Rules). However, I have some doubts:

1. At line 20 of the algorithm it is written that Ii has the same majority class than Ii+1. What is the meaning of this?

2. At line 20 of the algorithm it is written that there is a tie in Ii or Ii+1. A tie of what?

3. What is the requirement of line number 14 & 15 when line number 11 & 12 is covering all consecutive intervals?

Dear ResearchGater,

I'm trying to identify association between keywords in PubMed. The prototypic search could be : listing kinases (classified in term of number of publication) that are associated to the keyword cancer or inflammation. Does anybody have an idea of an easily accessible tool that can perform such search. Thank you for your help. 

Hello,

I want to find out how many modes are present in data distribution. As per my search I found many methods for testing whether a distribution is unimodal or multimodal but I am interested in finding out number of modes available in distribution. Can any one suggest me how to estimate this?

Can anyone tell me about real life live scenarios where Distributed Data Mining has been actually applied to wireless sensor networks in order to aid for decision making ?

I want to implement ECC algorithm in COOJA simulator and want to compare the performance of RSA and ECC in IoT(Internet of Things) nodes. I am using Contiki and Cooja.

I want to find out how possible it is to seamlessly integrate these technologies.

Thank you 

The data by T2 Hotelling  are assumed to be multivariate normal distribution.SVDD is  not strict  for data distribution. Therefore, for  non-gaussian data monitoring ,we should use SVDD monitoring. However, the monitoring effect of T2 is better than SVDD.What data  is SVDD more suitable for  monitoring?

In distributed data mining how we get knowledge using association rule when data is increasing frequently in each sites..

Distributed Association Rule Mining

There are numerous hypothetical examples of "Privacy Preservation in Distributed Data Mining" in literature. However, in practice can anyone give me scenarios where it has been actually applied?

I want to know about real case study of privacy threat cause of association rule mining (Distributed or centralized database).

In the following survey paper I found a comparison of some horizontal scaling platform and some vertical scaling platform. Now I want to make performance analysis of these platforms but I don't know whether there is any test bed available for such analysis.

I need the answer for the R-datamining tool . How much size it supports?

During any association mining process it is a big challenge to remove uninteresting rules. We are interested in effective formal and experimental method for finding interestingness of the multilevel rules.

If we have changed the source data, then do we have to follow the same step for finding/generating the rules? Or change the method?

I want to cluster the short tweets and predict the sentiments of the users in real time.

Given an auto-scaling system, we face inputs that have unpredictable patterns and volumes. Because they are allocated per input resource, fluctuations of input volume have much overhead of resource. Do you identify an algorithm that can help to systems performance?

In traditional parallel and distributed data mining algorithms the issues are data decomposition: data and task, data layout: horizontal and vertical, load balancing: static and dynamic, memory used: shared, distributed and hybrid. So if we design data mining algorithms on the MapReduce platform what should be the research issues?

I am working on Distributed Association Rule Mining. I need data sets to simulate my program on it.

I want to implement distributed association rule mining algorithms on either or both but don't know much about programming in grid or cloud environment.

Can anybody please help me to find some good survey/review paper on parallel and distributed association rule mining, grid based, and cloud based association rule mining?

Where to find these tools ?

What are the methods or best predictive methods to use for this kind of data?