Boongoen, T; Shen, Q; Price, C. 2011. FUZZY QUALITATIVE LINK ANALYSIS FOR ACADEMIC PERFORMANCE EVALUATION. INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 19 (3): 559-585

[K S Chudamani]

I have a similar paper published in 2008 in bombay science Library 
association conference. If you want I can send the details. I have used 
principal component analysis for arriving at primary classification 
secondary classification, etc.

Chudamani


On Fri, 8 Jul 2011, Eugene Garfield wrote:

> Adminstrative info for SIGMETRICS (for example unsubscribe):
> http://web.utk.edu/~gwhitney/sigmetrics.html
>
> Boongoen, T; Shen, Q; Price, C. 2011. FUZZY QUALITATIVE LINK ANALYSIS
> FOR ACADEMIC PERFORMANCE EVALUATION. INTERNATIONAL JOURNAL OF
> UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS 19 (3): 559-585.
>
> Author Full Name(s): Boongoen, Tossapon; Shen, Qiang; Price, Chris
> Language: English
> Document Type: Article
>
> Author Keywords: Academic performance evaluation; link analysis; order-of-
> magnitude reasoning; fuzzy sets
> KeyWords Plus: STUDENTS EVALUATION; CLASSIFICATION RULES; MEMBERSHIP
> FUNCTIONS; NUMBERS; SYSTEMS; LOGIC; SETS
>
> Abstract: Many approaches have been developed for academic performance
> evaluation using various fuzzy techniques. Initial methods rely greatly on
> experts specification of analytical parameters, without making use of valuable
> information embedded in collected data. Given this insight, fuzzy rule induction
> has recently been studied as a data-driven alternative. Despite its efficiency
> and reported performance, the fuzzy subsethood metric representing the
> strength of relations between system variables is only used at a coarse level,
> with the underlying semantics being Unfortunately distorted via a local cc
> scaling scheme. To overcome this problem, a novel fuzzy classification system
> is introduced in this paper, in which the existing measure is used to its full
> potential via the methodology of qualitative link analysis. With a network
> representation where variables and their relations are encoded as graph nodes
> and edges, the classification of a new instance conceptually becomes a
> problem of link-based similarity estimation that can be effectively resolved
> using the proposed fuzzy qualitative model. This new approach has been
> evaluated against the existing rule-based met hod, revealing significant
> advantages of the present work.
>
> Addresses: [Boongoen, Tossapon; Shen, Qiang; Price, Chris] Aberystwyth Univ,
> Dept Comp Sci, Aberystwyth SY23 SDB, Dyfed, Wales
> Reprint Address: Boongoen, T, Aberystwyth Univ, Dept Comp Sci, Aberystwyth
> SY23 SDB, Dyfed, Wales.
>
> E-mail Address: tsb at aber.ac.uk; qqs at aber.ac.uk; cjp at aber.ac.uk
> ISSN: 0218-4885
> DOI: 10.1142/S0218488511007131
> URL: http://www.worldscinet.com/ijufks/19/1903/S0218488511007131.html
>
>
>

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