International Journal on Soft Computing ( IJSC ): February 2022

Friday, 25 February 2022

Methodological Study Of Opinion Mining And Sentiment Analysis Techniques

Pravesh Kumar Singh and Mohd Shahid Husain, Integral University, India

ABSTRACT

Decision making both on individual and organizational level is always accompanied by the search of other’s opinion on the same. With tremendous establishment of opinion rich resources like, reviews, forum discussions, blogs, micro-blogs, Twitter etc provide a rich anthology of sentiments. This user generated content can serve as a benefaction to market if the semantic orientations are deliberated. Opinion mining and sentiment analysis are the formalization for studying and construing opinions and sentiments. The digital ecosystem has itself paved way for use of huge volume of opinionated data recorded. This paper is an attempt to review and evaluate the various techniques used for opinion and sentiment analysis.

KEYWORDS

Opinion Mining, Sentiment Analysis, Feature Extraction Techniques, Naïve Bayes Classifiers, Clustering, Support Vector Machines

Original Source URL: https://airccse.org/journal/ijsc/papers/5114ijsc02.pdf

https://airccse.org/journal/ijsc/current2014.html

Wednesday, 23 February 2022

International Journal on Soft Computing ( IJSC ), H index - Profile

International Journal on Soft Computing ( IJSC )

ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]

https://airccse.org/journal/ijsc/ijsc.html

Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com

International Journal on Soft Computing ( IJSC ), H index - Profile

https://www.academia.edu/72306933/International_Journal_on_Soft_Computing_IJSC_H_index_Profile

Academia: https://independent.academia.edu/IjscJournal/

Submission System: http://coneco2009.com/submissions/imagination/home.html

Monday, 21 February 2022

Call for Research Papers! February Issue!

International Journal on Soft Computing ( IJSC )

ISSN: 2229 - 6735 [Online] ; 2229 - 7103 [Print]

https://airccse.org/journal/ijsc/ijsc.html

Here's where you can reach us : ijscjournal@yahoo.com or ijsc@aircconline.com

Submission Deadline : February 26, 2022

Submission System: http://coneco2009.com/submissions/imagination/home.html

Friday, 18 February 2022

Integrating Vague Association Mining with Markov Model

Priya Bajaj and Supriya Raheja

Department of Computer Science & Engineering, ITM University Gurgaon, Haryana 122001, India

ABSTRACT

The increasing demand of World Wide Web raises the need of predicting the user’s web page request. The most widely used approach to predict the web pages is the pattern discovery process of Web usage mining. This process involves inevitability of many techniques like Markov model, association rules and clustering. Fuzzy theory with different techniques has been introduced for the better results. Our focus is on Markov models. This paper is introducing the vague Rules with Markov models for more accuracy using the vague set theory.

KEYWORDS

Fuzzy Logic, Fuzzy Mining Approach For Web Page Prediction, Prediction Techniques, Vague Logic, Vague Association Rule

Original Source URL: https://airccse.org/journal/ijsc/papers/5114ijsc01.pdf

https://airccse.org/journal/ijsc/current2014.html

Friday, 11 February 2022

An Efficient Method for Assessing Water Quality Based on Bayesian Belief Networks

Khalil Shihab1 and Nida Al-Chalabi2

1College of Engineering & Science, Victoria University, Australia

2Department of Computer Science, SQU, Oman

ABSTRACT

A new methodology is developed to analyse existing water quality monitoring networks. This methodology incorporates different aspects of monitoring, including vulnerability/probability assessment, environmental health risk, the value of information, and redundancy reduction. The work starts with a formulation of a conceptual framework for groundwater quality monitoring to represent the methodology’s context. This work presents the development of Bayesian techniques for the assessment of groundwater quality. The primary aim is to develop a predictive model and a computer system to assess and predict the impact of pollutants on the water column. The process of the analysis begins by postulating a model in light of all available knowledge taken from relevant phenomenon. The previous knowledge as represented by the prior distribution of the model parameters is then combined with the new data through Bayes’ theorem to yield the current knowledge represented by the posterior distribution of model parameters. This process of updating information about the unknown model parameters is then repeated in a sequential manner as more and more new information becomes available.

KEYWORDS

Bayesian Belief Networks, Water Quality Assessment, Data Mining

Original Source URL: https://airccse.org/journal/ijsc/papers/5214ijsc03.pdf

https://airccse.org/journal/ijsc/current2014.html

Friday, 4 February 2022

Design of Multiloop Controller for Three Tank Process Using CDM Techniques

N. Kanagasabai and N. Jaya, Annamalai University, India

ABSTRACT

In this study the controller for three tank multi loop system is designed using coefficient Diagram method. Coefficient Diagram Method is one of the polynomial methods in control design. The controller designed by using CDM technique is based on the coefficients of the characteristics polynomial of the closed loop system according to the convenient performance such as equivalent time constant, stability indices and stability limit. Controller is designed for the three tank process by using CDM Techniques; the simulation results show that the proposed control strategies have good set point tracking and better response capability.

KEYWORDS

Coefficient diagram method, three tank, multiloop, CDM-PI

Original Source URL: https://airccse.org/journal/ijsc/papers/5214ijsc02.pdf

https://airccse.org/journal/ijsc/current2014.html