Friday, 30 June 2023

Multi source feedback based performance appraisal system using Fuzzy logic decision support system

G.Meenakshi, Nalla Malla Reddy Engineering College, India

Abstract 

In Multi-Source Feedback or 360 Degree Feedback, data on the performance of an individual are collected systematically from a number of stakeholders and are used for improving performance. The 360-Degree Feedback approach provides a consistent management philosophy meeting the criterion outlined previously. The 360-degree feedback appraisal process describes a human resource methodology that is frequently used for both employee appraisal and employee development. Used in employee performance appraisals, the 360-degree feedback methodology is differentiated from traditional, top-down appraisal methods in which the supervisor responsible for the appraisal provides the majority of the data. Instead it seeks to use information gained from other sources to provide a fuller picture of employees’ performances. Similarly, when this technique used in employee development it augments employees’ perceptions of training needs with those of the people with whom they interact. The 360-degree feedback based appraisal is a comprehensive method where in the feedback about the employee comes from all the sources that come into contact with the employee on his/her job. The respondents for an employee can be her/his peers, managers, subordinates team members, customers, suppliers and vendors. Hence anyone who comes into contact with the employee, the 360 degree appraisal has four components that include self-appraisal, superior’s appraisal, subordinate’s appraisal student’s appraisal and peer’s appraisal .The proposed system is an attempt to implement the 360 degree feedback based appraisal system in academics especially engineering colleges. 

Keywords 

Multi source feed back, 360 degree feedback, performance appraisal system, fuzzy logic based decision support system for standards/rewards. 

Original Source URL: https://airccse.org/journal/ijsc/papers/2112ijsc08.pdf

https://airccse.org/journal/ijsc/current2012.html

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Contact Us: ijscjournal@yahoo.com or ijsc@aircconline.com

Submission System: https://airccse.com/submissioncs/home.html




Wednesday, 28 June 2023

11th International Conference of Artificial Intelligence and Fuzzy Logic (AI & FL 2023)

August 19 ~ 20, 2023, Chennai, India

https://cse2023.org/aifl/index

Paper Submission

Authors are invited to submit papers through the Submission System by July 01, 2023.

Submission Link: https://cse2023.org/submission/index.php

Contact Us: aifl@cse2023.org



Monday, 26 June 2023

Call for Research Papers! August Issue!

International Journal on Soft Computing (IJSC)

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

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

Submission Deadline: July 01, 2023

Contact Us:  ijscjournal@yahoo.com or ijsc@aircconline.com

Paper Submission URL - https://airccse.com/submissioncs/home.html 




Friday, 23 June 2023

International Journal on Soft Computing (IJSC)

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

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

Submission Deadline: July 01, 2023

Contact Us:  ijscjournal@yahoo.com or ijsc@aircconline.com

Paper Submission URL - https://airccse.com/submissioncs/home.html 

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




Tuesday, 20 June 2023

Friday, 16 June 2023

Current Issue - May 2023, Volume 14, Number 2

 May 2023, Volume 14, Number 2

Texts Classification with the usage of Neural Network based on the Word2vec’s Words Representation 

D. V. Iatsenko, Southern Federal University, Russia

ABSTRACT

Assigning the submitted text to one of the predetermined categories is required when dealing with application-oriented texts. There are many different approaches to solving this problem, including using neural network algorithms. This article explores using neural networks to sort news articles based on their category. Two word vectorization algorithms are being used — The Bag of Words (BOW) and the word2vec distributive semantic model. For this work the BOW model was applied to the FNN, whereas the word2vec model was applied to CNN. We have measured the accuracy of the classification when applying these methods for ad texts datasets. The experimental results have shown that both of the models show us quite the comparable accuracy. However, the word2vec encoding used for CNN showed more relevant results, regarding to the texts semantics. Moreover, the trained CNN, based on the word2vec architecture, has produced a compact feature map on its last convolutional layer, which can then be used in the future text representation. I.e. Using CNN as a text encoder and for learning transfer.

KEYWORDS

Deep Learning, Text classification, Word2Vec, BOW, CNN

Original Source URL: https://aircconline.com/ijsc/V14N2/14223ijsc01.pdf

https://airccse.org/journal/ijsc/current2023.html




Monday, 12 June 2023

Submit Your Research Articles! August Issue Journal!

International Journal on Soft Computing (IJSC)

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

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

Contact Us:  ijscjournal@yahoo.com or ijsc@aircconline.com

Paper Submission URL - https://airccse.com/submissioncs/home.html

Submission Deadline: June 21, 2023



February Issue Journal! Authors are invited to submit papers!

International Journal on Soft Computing (IJSC) ISSN: 2229 - 6735 [Online]; 2229 - 7103 [Print] https://airccse.org/journal/ijsc/ijsc.html He...