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Sentiment Analysis Framework Development

We ar looking for a social network sentiment analysis expert. The expert should have background in natural languge processing, data mining (text mining) and machine learning algorithms.

The development platform can be selected among any programming language, but Java is preferred. The project requires to develop a novel hybrid sentiment analysis framework with machine learning algorithms. The implementations of some algorithms may be added from existing implementations from Weka or anyother open source software to the developed platform.

The platform should be compatible to different datasets. The platform should allow user to change the configuration of the model easily. For example, changing the classification algorithm of Naive bayes with another classifier should be easily changed.

The developed framework should outperform existing sentiment analysis classifiers in terms of accuracy, precision, etc. metrics. The framework will be tested on several (4-5 different) sentiment benchmark data sets, such as twitter, movie recommendation, etc.

Sample plan for the project is given below: Other plan suggestions are welcome, but the total project deadline is 9 months max and budget is confined to 3000$. Please keep these considerations in mind.

The coder is also expected to submit a "Progress report" at the end of each month.

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Milestones Description

Month 1 Analysis & Propose of Algorithm, Identification of Existing Algorithms, Ensemble Techniques, Identification of Datasets to be used.

Month 2 Implementation and Results of Algorithm 1

Month 3 Implementation and Results of Algorithm 2

Month 4 Implementation and Results of Algorithm 3

Month 5 Implementation and Results of Ensemble Technique 1

Month 6 Implementation and Results of Ensemble Technique 2

Month 7 Implementation and Results of Ensemble Technique 3

Month 8 Comparison of Results of the Individual Algorithms and Ensemble Techniques

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Skills: Data Mining, Machine Learning

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About the Employer:
( 20 reviews ) 1, Turkey

Project ID: #5380390

7 freelancers are bidding on average $2878 for this job

alphaedge999

Hello there, Very interested in this study. I have been involved in a couple of social network analysis projects as well as NLP projects. Please feel free to contact me for details. I would like to use JAVA for this More

$3000 USD in 90 days
(1 Review)
4.6
antfilfon

Very interested in this project. I will do it like I did with the ant clustering algorithm implemented in Java.

$3000 USD in 3 days
(1 Review)
3.2
oaliosl

Hi, I am Developer with experience of web and mobile developement. I have worked on Ai too. Please msg me. I am online. Thanks

$3000 USD in 270 days
(0 Reviews)
0.0
aminhosseiny

Hello sir. I think I could help you through your big project. I'm postgraduate of artificial Intelligence with good background of data-mining. I have had several experiments of text mining and a lot of study on opinio More

$3000 USD in 180 days
(0 Reviews)
0.0
raiseq

HI. I can help you to build based on opensource java platform which can enable you to do the sentiment analysis using big data from Twitters, blogs etc... 1. able to ... natural language processing, data mining ( More

$3092 USD in 250 days
(0 Reviews)
0.0
masterabhijit

Hi, I am in my 3rd year of PhD in NLP (working on SA) and I am well versed with Machine Learning. I have already managed to implement an ensemble of classifiers for SA viz. A rule Based Classifier, and Statistical cla More

$2222 USD in 180 days
(0 Reviews)
0.0
twell

Hi, I believe I am the guy you are looking for. I am currently a PHD student on Machine Learning, specifically on data mining and deep learning. In addition, I have two working experience on big software company workin More

$2888 USD in 120 days
(0 Reviews)
0.0
helmot

Hello. I was working on a similar project a couple of years ago. I have a Msc degree in AI and my thesis was about data mining and web mining applications. I have worked in text processing applications in several doma More

$2947 USD in 30 days
(0 Reviews)
0.0