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ICACT20220156 Question.1
Questioner: tomayoon@ieee.org    2022-02-15 오후 12:43:36 		ICACT20220156 Answer.1
Answer by Auhor faryal.nosheen@ceme.nust.edu.pk   2022-02-15 오후 12:43:36
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First of all, thank you for the good research paper and presentation contents. I would like to know more about the research environment used in this study, and also in detail about the equipment & operating systems, development languages and software libraries you used. Thank you for your question. Operating system is Windows 10 with following hardware specifications: Processor x64, generation i-78550U, memory 16GB, cache 8M. I have used Python to implement the algorithm and software libraries include Openpyxl, Scikit-Learn, Numpy and many other standard libraries of python.
ICACT20220156 Question.2
Questioner: tomayoon@ieee.org    2022-02-15 오후 12:57:11 		ICACT20220156 Answer.2
Answer by Auhor faryal.nosheen@ceme.nust.edu.pk   2022-02-15 오후 12:57:11
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Will you tell us what is the major achievement of this paper, and also what is further study issue from this? Thanks in advance!! Major achievement of this paper includes 1) Considering preference relation of attributes, we explore proposition based incremental technique to update approximations of DRSA upon insertion of new objects, in time efficient manner. 2) A dynamic method to update approximations of DRSA upon deletion of objects which is computationally efficient. 3) Along with dynamic algorithms for maintaining approximations, experiments are carried out to evaluate the advantages of the proposed approach. The experimental results of comparison of our proposed approach with conventional DRSA algorithm and another recent incremental method, showed that our proposed technique successfully update approximations in reduce time, without compromising accuracy. This shows that our method can be used successfully for dynamic applications which based on DRSA approximations. In this study, we explored single dimension variation in dataset and update approximations by assuming that conditional and decisional attribute set along with value set of conditional and decision attribute remained unchanged. In future, we want to enhance its functionality to handle multi-dimensional variations i.e., variation in conditional attribute set, decision attribute set and value set of conditional and decision attribute.
ICACT20220156 Question.3
Questioner: donnangtoan@gmail.com    2022-02-15 오후 4:26:09 		ICACT20220156 Answer.3
Answer by Auhor faryal.nosheen@ceme.nust.edu.pk   2022-02-15 오후 4:26:09
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You have done a interesting research. What are heuristics here? What problems does your solution solve in the real environment? Thank you. Thank you for your remarks. Heuristic approach based on solving problem with good solution along with extensive experimental evaluations. In other words we can say that heuristic approach provides a fair solution in a shorter execution time. In this paper, we have proposed heuristic rules to compute approximations without going through the lengthy computational steps of traditional DRSA algorithm and we achieved considerable reduction in execution time. Our rules based on the definitions of preliminaries of dominance based rough set theory and properties of approximations. We avoid lengthy comparisons and repetitions by using these rules which ultimately reduce computational cost in terms of time. We have performed experiments on UCI datasets, extensively, to judge the performance of proposed heuristic approach, in comparison with static and non-static techniques. By using this approach, we consequently reducing computational cost of all subsequent tasks based on approximations i.e., decision rule generations, reduct generations, classification, prediction etc. Our approach proposed a mechanism to update approximations in dynamic environment, much more efficiently. For example, in real environment, we can use proposed method to update the information regarding bankrupt chances of companies by analyzing preference ordered data in dynamic environment and for many other multi-criteria classification applications in real time environment.
ICACT20220156 Question.4
Questioner: namacabale@gmail.com    2022-02-16 오후 2:19:44 		ICACT20220156 Answer.4
Answer by Auhor faryal.nosheen@ceme.nust.edu.pk   2022-02-16 오후 2:19:44
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Dear Author, you have a very good research. Is the technology today capable of implementing your proposed scheme? Is there an existing technology almost similar to your proposal that has been deployed in real world environment? Thank you and stay safe. Thank you for your encouragement. Technology is available to implement this approach in real world environment. Any good system which can run any other algorithm, can be implemented it and performance of our proposed technique depends on system specifications. Its basic contribution is reduction in execution time, require for updating DRSA approximations and it ultimately reduces the time require to get updated information for decision making, classification, prediction etc. Similar approaches have been deployed in real-world environment and few has been mentioned in related work section of our paper.