How to cite this paper
Karimi-Majd, A & Fathian, M. (2017). Extracting new ideas from the behavior of social network users.Decision Science Letters , 6(3), 207-220.
Refrences
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Au, W. H., & Chan, K. C. (2003). Mining fuzzy association rules in a bank-account database. IEEE Transactions on Fuzzy Systems, 11(2), 238-248.
Bae, J. K., & Kim, J. (2011). Product development with data mining techniques: A case on design of digital camera. Expert Systems with Applications, 38(8), 9274-9280.
Carmagnola, F., Vernero, F., & Grillo, P. (2013). Advanced Social Recommendations with SoNARS++. Interacting with Computers, iwt028.
Cena, F., Likavec, S., Lombardi, I., & Picardi, C. (2016). Should I Stay or Should I Go? Improving Event Recommendation in the Social Web. Interacting with Computers, 28(1), 55-72.
Cheng, L. C., & Sun, L. M. (2012). Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: An empirical case study. Electronic Commerce Research and Applications, 11(2), 89-100.
De Souza, C. S., & Preece, J. (2004). A framework for analyzing and understanding online communities. Interacting with Computers, 16(3), 579-610.
Deng, S., Huang, L., & Xu, G. (2014). Social network-based service recommendation with trust enhancement. Expert Systems with Applications, 41(18), 8075-8084.
Donath, W. E., & Hoffman, A. J. (1973). Lower bounds for the partitioning of graphs. IBM Journal of Research and Development, 17(5), 420-425.
Erdös, P., & Rényi, A. (1959). On random graphs, I. Publicationes Mathematicae (Debrecen), 6, 290-297.
Feng, X., Sharma, A., Srivastava, J., Wu, S., & Tang, Z. (2016). Social network regularized Sparse Linear Model for Top-N recommendation. Engineering Applications of Artificial Intelligence, 51, 5-15.
Flint, D. J. (2002). Compressing new product success-to-success cycle time: Deep customer value understanding and idea generation. Industrial marketing management, 31(4), 305-315.
Franceschini, F. (2016). Advanced quality function deployment. CRC Press.
Han, I., & Kamber, M. (2006). Data mining concepts and techniques. Morgan Kaufinann.
Jaccard, P. (1901). Distribution de la florine alpine dans la bassin de danses. et dans quelques regions voisines. Naturelles Bulletin de la Societe Vaudoise des Sciences, 241–272.
Karimi-Majd, A. M., Fathian, M., & Amiri, B. (2015). A hybrid artificial immune network for detecting communities in complex networks. Computing, 97(5), 483-507.
Karimi-Majd, A. M., & Mahootchi, M. (2015). A new data mining methodology for generating new service ideas. Information Systems and e-Business Management, 13(3), 421-443.
Kumar, S., & Phrommathed P. (2005). New product development: an empirical study of the effects of innovation strategy, organization learning and market conditions. Springer, New York.
Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use. Computers in human behavior, 26(2), 254-263.
Lee, C. K. H., Tse, Y. K., Ho, G. T., & Choy, K. L. (2015). Fuzzy association rule mining for fashion product development. Industrial Management & Data Systems, 115(2), 383-399.
Liao, S. H., Hsieh, C. L., & Huang, S. P. (2008). Mining product maps for new product development. Expert Systems with Applications, 34(1), 50-62.
Liao, S. H., Chen, Y. N., & Tseng, Y. Y. (2009). Mining demand chain knowledge of life insurance market for new product development. Expert Systems with Applications, 36(5), 9422-9437.
Liao, S. H., Chen, Y. J., & Deng, M. Y. (2010). Mining customer knowledge for tourism new product development and customer relationship management. Expert Systems with Applications, 37(6), 4212-4223.
Liu, D. R., & Shih, Y. Y. (2005). Integrating AHP and data mining for product recommendation based on customer lifetime value. Information & Management, 42(3), 387-400.
Niyagas, W., Srivihok, A., & Kitisin, S. (2006). Clustering e-banking customer using data mining and marketing segmentation. ECTI Transactions on Computer and Information Technology (ECTI-CIT), 2(1), 63-69.
Osborn, A. F. (1953). Applied imagination, principles and procedures of creative thinking.
Park, H. S., & Jun, C. H. (2009). A simple and fast algorithm for K-medoids clustering. Expert Systems with Applications, 36(2), 3336-3341.
Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics, 20, 53-65.
Strehl, A., Ghosh, J., & Mooney, R. (2000, July). Impact of similarity measures on web-page clustering. In Workshop on Artificial Intelligence for Web Search (AAAI 2000) (pp. 58-64).
Sznajd-Weron, K., & Sznajd, J. (2000). Opinion evolution in closed community. International Journal of Modern Physics C, 11(06), 1157-1165.
Tang, L., & Liu, H. (2010). Community detection and mining in social media. Synthesis Lectures on Data Mining and Knowledge Discovery, 2(1), 1-137.
Thorleuchter, D., Van den Poel, D., & Prinzie, A. (2010, January). Extracting consumers’ needs for new products-A web mining approach. In Knowledge Discovery and Data Mining, 2010. WKDD'10. Third International Conference on (pp. 440-443). IEEE.
Yigit, M., Bilgin, B. E., & Karahoca, A. (2015). Extended topology based recommendation system for unidirectional social networks. Expert Systems with Applications, 42(7), 3653-3661.
Zanghi, H., Volant, S., & Ambroise, C. (2010). Clustering based on random graph model embedding vertex features. Pattern Recognition Letters, 31(9), 830-836.
Zhu, Z., Su, J., & Kong, L. (2015). Measuring influence in online social network based on the user-content bipartite graph. Computers in Human Behavior, 52, 184-189.
Au, W. H., & Chan, K. C. (2003). Mining fuzzy association rules in a bank-account database. IEEE Transactions on Fuzzy Systems, 11(2), 238-248.
Bae, J. K., & Kim, J. (2011). Product development with data mining techniques: A case on design of digital camera. Expert Systems with Applications, 38(8), 9274-9280.
Carmagnola, F., Vernero, F., & Grillo, P. (2013). Advanced Social Recommendations with SoNARS++. Interacting with Computers, iwt028.
Cena, F., Likavec, S., Lombardi, I., & Picardi, C. (2016). Should I Stay or Should I Go? Improving Event Recommendation in the Social Web. Interacting with Computers, 28(1), 55-72.
Cheng, L. C., & Sun, L. M. (2012). Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: An empirical case study. Electronic Commerce Research and Applications, 11(2), 89-100.
De Souza, C. S., & Preece, J. (2004). A framework for analyzing and understanding online communities. Interacting with Computers, 16(3), 579-610.
Deng, S., Huang, L., & Xu, G. (2014). Social network-based service recommendation with trust enhancement. Expert Systems with Applications, 41(18), 8075-8084.
Donath, W. E., & Hoffman, A. J. (1973). Lower bounds for the partitioning of graphs. IBM Journal of Research and Development, 17(5), 420-425.
Erdös, P., & Rényi, A. (1959). On random graphs, I. Publicationes Mathematicae (Debrecen), 6, 290-297.
Feng, X., Sharma, A., Srivastava, J., Wu, S., & Tang, Z. (2016). Social network regularized Sparse Linear Model for Top-N recommendation. Engineering Applications of Artificial Intelligence, 51, 5-15.
Flint, D. J. (2002). Compressing new product success-to-success cycle time: Deep customer value understanding and idea generation. Industrial marketing management, 31(4), 305-315.
Franceschini, F. (2016). Advanced quality function deployment. CRC Press.
Han, I., & Kamber, M. (2006). Data mining concepts and techniques. Morgan Kaufinann.
Jaccard, P. (1901). Distribution de la florine alpine dans la bassin de danses. et dans quelques regions voisines. Naturelles Bulletin de la Societe Vaudoise des Sciences, 241–272.
Karimi-Majd, A. M., Fathian, M., & Amiri, B. (2015). A hybrid artificial immune network for detecting communities in complex networks. Computing, 97(5), 483-507.
Karimi-Majd, A. M., & Mahootchi, M. (2015). A new data mining methodology for generating new service ideas. Information Systems and e-Business Management, 13(3), 421-443.
Kumar, S., & Phrommathed P. (2005). New product development: an empirical study of the effects of innovation strategy, organization learning and market conditions. Springer, New York.
Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use. Computers in human behavior, 26(2), 254-263.
Lee, C. K. H., Tse, Y. K., Ho, G. T., & Choy, K. L. (2015). Fuzzy association rule mining for fashion product development. Industrial Management & Data Systems, 115(2), 383-399.
Liao, S. H., Hsieh, C. L., & Huang, S. P. (2008). Mining product maps for new product development. Expert Systems with Applications, 34(1), 50-62.
Liao, S. H., Chen, Y. N., & Tseng, Y. Y. (2009). Mining demand chain knowledge of life insurance market for new product development. Expert Systems with Applications, 36(5), 9422-9437.
Liao, S. H., Chen, Y. J., & Deng, M. Y. (2010). Mining customer knowledge for tourism new product development and customer relationship management. Expert Systems with Applications, 37(6), 4212-4223.
Liu, D. R., & Shih, Y. Y. (2005). Integrating AHP and data mining for product recommendation based on customer lifetime value. Information & Management, 42(3), 387-400.
Niyagas, W., Srivihok, A., & Kitisin, S. (2006). Clustering e-banking customer using data mining and marketing segmentation. ECTI Transactions on Computer and Information Technology (ECTI-CIT), 2(1), 63-69.
Osborn, A. F. (1953). Applied imagination, principles and procedures of creative thinking.
Park, H. S., & Jun, C. H. (2009). A simple and fast algorithm for K-medoids clustering. Expert Systems with Applications, 36(2), 3336-3341.
Rousseeuw, P. J. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics, 20, 53-65.
Strehl, A., Ghosh, J., & Mooney, R. (2000, July). Impact of similarity measures on web-page clustering. In Workshop on Artificial Intelligence for Web Search (AAAI 2000) (pp. 58-64).
Sznajd-Weron, K., & Sznajd, J. (2000). Opinion evolution in closed community. International Journal of Modern Physics C, 11(06), 1157-1165.
Tang, L., & Liu, H. (2010). Community detection and mining in social media. Synthesis Lectures on Data Mining and Knowledge Discovery, 2(1), 1-137.
Thorleuchter, D., Van den Poel, D., & Prinzie, A. (2010, January). Extracting consumers’ needs for new products-A web mining approach. In Knowledge Discovery and Data Mining, 2010. WKDD'10. Third International Conference on (pp. 440-443). IEEE.
Yigit, M., Bilgin, B. E., & Karahoca, A. (2015). Extended topology based recommendation system for unidirectional social networks. Expert Systems with Applications, 42(7), 3653-3661.
Zanghi, H., Volant, S., & Ambroise, C. (2010). Clustering based on random graph model embedding vertex features. Pattern Recognition Letters, 31(9), 830-836.
Zhu, Z., Su, J., & Kong, L. (2015). Measuring influence in online social network based on the user-content bipartite graph. Computers in Human Behavior, 52, 184-189.