Fuzzy indexing and retrieval in case-based systems

Jeng, Bing Chiang; Liang, Ting‐Peng

doi:10.1016/0957-4174(94)e0004-e

Cited by 70 publications

(26 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This technique is an alternative to an expert system, which is based on rule-based reasoning. Essential tasks to make a typical CBR system are: (1) retrieve one or a small set of the most similar cases according to the problem specification; (2) adapt to the new situation by revising former solutions; (3) retain the new case and solution as part of history for future retrievals (Jeng & Liang, 1995).…”

Section: Case-based Reasoning (Cbr)mentioning

confidence: 99%

A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance improvement

Juan

2009

Expert Systems with Applications

View full text Add to dashboard Cite

Section: Case-based Reasoning (Cbr)mentioning

confidence: 99%

A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance improvement

Juan

2009

Expert Systems with Applications

View full text Add to dashboard Cite

“…Once the term set is generated, it can be used to fuzzify a numeric value into a fuzzy value with some degree of belonging. Jeng and Liang 13 have shown this idea of fuzzy retrieval in case-based systems, except that they defined the term set in a heuristic way. The fuzzified data can subsequently be used to induce fuzzy classification rules.…”

Section: Potential Applicationsmentioning

confidence: 99%

A fuzzy c-medians variant for the generation of fuzzy term sets

Liao

2002

Int. J. Intell. Syst.

View full text Add to dashboard Cite

A fuzzy c-medians variant is proposed for the generation of fuzzy term sets with one half overlap. The proposed variant is modified from the original algorithm mainly in two areas. The first modification ensures that two end terms take the maximum and minimum domain values as their centers. The second modification prevents the generation of non-convex fuzzy terms that often are obtained by the original algorithm. The optimal number of terms and the optimal shape of membership function associated with each term are determined based on the mean squared error criterion. The exponential weight, m, used in the algorithm is found to greatly affect the shape of membership function. The effect of data size used for the generation of fuzzy terms is also discussed. A generalized s-shaped function with a tunable parameter along with its complement (i.e., a generalized z-shaped function with a tunable parameter) is developed to fit all term sets generated by the fuzzy c-medians variant using various m values.

show abstract

“…Transactive memory system (TMS) refers to a shared mental mode of the collective indicating which individuals know certain things and which individuals know who knows certain things (Jarvenpaa and Majchrzak, 2008) and it encompasses encoding, storage, and retrieval of knowledge from different spheres (Wegner et al, 1987) Through building a transactive memory system specialization of knowledge together with trust in knowledge of others and knowledge coordination according to the task structure are achieved (Wegner et al,1987). Elements of knowledge sharing, such us feedback, communication influence the development of TMS (Hollingshead 1998a(Hollingshead , 1998bMoreland et al, 1996) which in turn enhances team performance (Liang et al, 1995;Lewis & Kyle, 2004;Kanawattanachai & Yoo, 2002;Faraj & Sproull, 2000).…”

Section: Tacit Knowledge Sharingmentioning

confidence: 99%

The value of knowledge sharing: impact of tacit and explicit knowledge sharing on team performance of scientists

Obrenovic

Hudaykulov

2015

IJMSBA

View full text Add to dashboard Cite

Knowledge sharing that takes place among team members is a process of great relevance that builds ties and relationships which in turn results in positive organizational and team outcomes. However, as it is not usually formally included in the job descriptions and is not a formal part of organizations’ and team activities, it is considered to be an organization citizenship behavior. Our paper emphasizes significance of tacit and explicit knowledge sharing to team performance in the context of scientific cooperation. Positive relationship between tacit knowledge sharing and explicit knowledge sharing with team performance was found using linear regression. Furthermore, high levels of knowledge sharing and team performance were identified among scientists.

show abstract

Fuzzy indexing and retrieval in case-based systems

Cited by 70 publications

References 11 publications

A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance improvement

A hybrid approach using data envelopment analysis and case-based reasoning for housing refurbishment contractors selection and performance improvement

A fuzzy c-medians variant for the generation of fuzzy term sets

The value of knowledge sharing: impact of tacit and explicit knowledge sharing on team performance of scientists

Contact Info

Product

Resources

About