Neuro Fuzzy based user queries categorization

Khan, Shoeb; Khodke, P. A.; Bhagat, Amit

doi:10.1109/iciiecs.2015.7193133

“…Trailing on, the development of an adaptive information filtering system using Adaptive Neural Fuzzy Inference Systems (ANFIS) was done in the research study concluded by [32]. The procedure of personnel assortment of candidates was automated based on specific Human Resource criterion of skills, vacancies and experience.…”

Section: B Adaptive Neuro Fuzzy Inference Systems (Anfis) Used For Hr Recruitment and Selectionmentioning

confidence: 99%

A Hybrid Model to Profile and Evaluate Soft Skills of Computing Graduates for Employment

Ramalingam¹,

Usmani²,

Hashem³

et al. 2021

IJACSA

0

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Emerging tools such as Game Based Assessments have been valuable in talent screening and matching soft skills for job selection. However, these techniques/models are rather stand alone and are unable to provide an objective measure of the effectiveness of their approach leading to mismatch of skills. In this research study, we are proposing a Theoretical Hybrid Model, combining aspects of Artificial Intelligence and Game Based Assessment in profiling, assessing and ranking graduates based on their soft skills. Firstly, an Intelligent Controller is used to extract and classify the graduate skill profile based on data findings extracted using traditional assessment methods of self-evaluation and interview. With motivation and engagement as a competitive difference, an existing Game Based Assessment (OWIWI) is then used to assess the soft skills of these graduates hence generating a Graduate Profile based on results of the game. Moving forward, a ranking technique is then applied to match the profile to selected job requirements based on soft skills required for the job and the graduate strength. Finally, a comparison analysis is concluded based on the soft skills profile obtained before employment (pre-employment) and objective measure feedback of soft skills obtained after employment (post-employment) to provide a validity check to study the effectiveness of the overall Hybrid Model. Specifically, data obtained from this study can be useful in solving issues of unemployment due to mismatch of soft skills at the Higher Learning Institution level.

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Hybrid Fuzzy Neural Search Retrieval System

Ghnemat

¹

,

Shaout

²

2017

Fuzzy Systems

1

0

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Search engines are crucial for information gathering systems (IGS). New challenges face search engines concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the search process. Based on a Multilayer Fuzzy Inference System (MFIS), the first step is to implement a scalable system to relay logical rules in order to produce three classifications for search behavior, user profiles, and query characteristics from analysis of navigation log files. These three outputs from the MFIS are used as inputs for the second step, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The training process of the ANFIS replaced the rules by adjusting the weights in order to find the most relevant result for the search query. This proposed system, called MFIS-ANFIS, is implemented as an experimental system. The system performance is evaluated using quantitative and comparative analysis. MFIS-ANFIS aimed to be the core of intelligent and reliable search process.

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Hybrid Fuzzy Neural Search Retrieval System

Ghnemat

¹

,

Shaout

²

2022

International Journal of Enterprise Information Systems

3

0

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Search engines are crucial for information gathering systems (IGS). New challenges face search engines concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the search process. Based on a Multilayer Fuzzy Inference System (MFIS), the first step is to implement a scalable system to relay logical rules in order to produce three classifications for search behavior, user profiles, and query characteristics from analysis of navigation log files. These three outputs from the MFIS are used as inputs for the second step, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The training process of the ANFIS replaced the rules by adjusting the weights in order to find the most relevant result for the search query. This proposed system, called MFIS-ANFIS, is implemented as an experimental system. The system performance is evaluated using quantitative and comparative analysis. MFIS-ANFIS aimed to be the core of intelligent and reliable search process.

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Neuro Fuzzy based user queries categorization

Cited by 3 publications

References 21 publications

A Hybrid Model to Profile and Evaluate Soft Skills of Computing Graduates for Employment

A Hybrid Model to Profile and Evaluate Soft Skills of Computing Graduates for Employment

Hybrid Fuzzy Neural Search Retrieval System

Hybrid Fuzzy Neural Search Retrieval System

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