Software for Feedback System Using Adaptive Categorization and Authenticated Recommendation

Software for Feedback System Using Adaptive Categorization and Authenticated Recommendation

Ayan Banerjee (Computer Innovative Research Society, Howrah, India) and Anirban Kundu (Information Technology Department, Netaji Subhash Engineering College, Kolkata, India & Innovation Research Lab (IRL), Howrah, India)
Copyright: © 2019 |Pages: 33
DOI: 10.4018/IJOSSP.2019040103
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The authors propose a web-based adaptive categorization and authenticated recommendation system, based on teacher performance. Distinct layers of the proposed framework have been operated from many geographically distributed locations. The system contains multiple entry points such as a student attendance module, a teacher categorization module, and a teacher recommendation module, strictly accessed by the administrative authority of an academic organization. The student attendance module is required for achieving better results on the teacher categorization module, and the teacher recommendation module. The reliability factor has been incorporated for realizing the accuracy of the proposed system. The administration authorities communicate with the server to categorize and recommend teachers by using teachers' performance. The replication and re-allocation transparencies have been maintained throughout the servers. Lightweight system performance has been enhanced due to the incorporation of a paperless approach and has provided less data loss. A linear time complexity is achieved due to usage of cellular automata as a tool.
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IT resources have been securely stored into a centralized zone of web. IT resources have been sharable to users of any geographically different locations in a distributed manner concurrently through web-services. Performance of web-services has been successfully done within a heterogeneous scalable computer network. Flexibility and scalability have been increased due to incorporation of the accessibility of multi-user mode. Multiple users of Adaptive Teacher Categorization and Recommendation System have been allowed to access the similar interface designed by researchers. All network related set up has been done in server-side network (Gamaleldin, 2013; Kumar & Goudar, 2012; Nazir, 2012; Dillon et al., 2010).

Now-a-days, any online transaction processing should be performed through sharable database. Data collection has been partitioned in horizontal and vertical manners, and a distributed workload has been represented across the nodes in load balanced cluster (Chen et al., 2015). Amount of data should be distributed over network-based database management system due to maintenance a cost-effective approach and rapid enhancement of network technology. Replication technique over the network has helped to control the data loss of distributed database (Gelogo & Lee, 2012; Kundu et al., 2014; Ratawa et al., 2017; Kundu et al., 2012).

Major and Minor Objectives

Major objective of this research work is to build up a web based multi-user system for performing categorization of teachers, and further recommend best possible solution to select a teacher for a particular subject based on performance analysis.

Minor objectives are to exhibit linear time and space complexities for proposed system.


Scope of the system is teachers’ categorization and recommendation of an academic organization using teacher performance information. Adaptive approach is typically a one way communication, and is applicable in other applications such as hospital management system, office management system and so on. Performance of proposed system is shown using efficient algorithms having linear complexities.


Teachers’ categorization and recommendation system has been utilized to categorize teachers depending on teachers’ performance and to allocate suitable subjects for each particular teacher of an academic organization. Analysis of categorization and recommendation procedures should be performed without human interference. Web based approach has been incorporated to access the proposed system from each position of planet.


Rest of the paper is organized as follows: In literature review section, past researches and challenges have been discussed. In cellular automata preliminaries section, cellular automata related preliminary discussion have been discussed; In background section earlier work has been elaborated along with required figures; Overview of proposed system has been presented along with proposed algorithms in overall description of proposed system section; Design framework of proposed modules such as student attendance module, teacher categorization module, and teacher recommendation module have been elaborated exhibiting all the required figures of activities and database oriented connections along with proposed algorithms; In theoretical discussion section, theorem have been established along with theoretical discussions. In hypothetical analysis section, theoretical analysis of proposed system has been presented along with all required figures; In proficiency analysis section, comparative analysis between existing systems and proposed system has been depicted. In cellular automata mapping with proposed system, necessity of cellular automata at proposed system has been described along with required figure; In experimental results section, experimental analysis has been shown to establish real time performance of faculty members of an institution.

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