A Hybrid Approach for Knowledge Recommendation

Wen-Yau Liang ； Chun-Che Huang ； Yu-Ting Pan

《International Journal of Information and Management Sciences》 27卷1期 (2016/03) Pp. 17-39

https://doi.org/10.6186/IJIMS.2016.27.1.2

並列摘要

Knowledge sharing is critical to knowledge management as it enables employees to share their knowledge. However, knowledge searching is a very time-consuming work. Additionally, in the context of an unsolved puzzle or unknown task, users typically have to determine the knowledge for which they will search. Therefore, knowledge management platforms for enterprises should have knowledge recommendation functionality. Hybrid recommendation systems (RS) have been developed to overcome, or at least to mitigate, the limitations of collaborative filtering. Because Genetic Algorithm (GA) is good at searching, it can cluster data according to similarities. However, the increase in the amount of data and information reduces the performance of a GA, thereby increasing cost of finding a solution. This work applies a novel method for incorporating a GA and rough set theory into clustering. In this paper, this work presents a hybrid knowledge recommendation model, which has a two-phase model for clustering and recommending. Approach implementation is demonstrated, as are its effectiveness and efficiency.

並列關鍵字

Knowledge recommendation ； clustering techniques ； rough set theory ； genetic algorithm

參考文獻

Anzanello, M. J.,Fogliatto, F. S.(2011).Selecting the best clustering variables for grouping mass-customized products involving workers' learning.International Journal of Production Economics.130,287-299.

Azadeh, A.,Saberi, M.,Anvari, M.,Azaron, A.,Mohammadi, M.(2011).An adaptive network based fuzzy inference system-genetic algorithm clustering ensemble algorithm for performance as-sessment and improvement of conventional power plants.Expert Systems with Applications.38,2224-2234.

Barragáns-Mart?nez, A. B.,Costa-Montenegro, E.,Burguillo, J. C.,Rey-López, M.,Mikic-Fonte, F. A.,Peleteiro, A.(2010).A hybrid content-based and item-based collaborative filtering approach to recommend TV programs enhanced with singular value decomposition.Information Sciences.180,4290-4311.

Blanco-Fernández, Y.,López-Nores, M.,Gil-Solla, A.,Ramos-Cabrer, M.,Pazos-Arias, J. J.(2011).Exploring synergies between content-based filtering and Spreading Activation techniques in knowledge-based recommender systems.Information Sciences.181,4823-4846.

Bjørnson, F. O.,Dingsøyr, T.(2008).Knowledge management in software engineering: A sys-tematic review of studied concepts, findings and research methods used.Information and Software Technology.50,1055-1068.