Aggarwal, C. C., & Zhai, C. (2012). Mining text data. Springer Science & Business Media.
Aguwa, C., Olya, M. H., & Monplaisir, L. (2017). Modeling of fuzzy-based voice of customer for business decision analytics. Knowledge-Based Systems, 125, 136-145.
Alkahtani, M., Choudhary, A., De, A., & Harding, J. A. (2019). A decision support system based on ontology and data mining to improve design using warranty data. Computers & Industrial Engineering, 128, 1027-1039.
Alzate, M., Arce-Urriza, M., & Cebollada, J. (2022). Mining the text of online consumer reviews to analyze brand image and brand positioning. Journal of Retailing and Consumer Services, 67, 102989.
Bodendorf, F., & Kaiser, C. (2010). Mining Customer Opinions on the Internet-A case study in the Automotive Industry. 2010 Third International Conference on Knowledge Discovery and Data Mining,
Budgen, D., Turner, M., Brereton, P., & Kitchenham, B. A. (2008). Using Mapping Studies in Software Engineering. PPIG,
Chang, D., & Chen, C.-H. (2014). Exploration of a Concept Screening Method in a Crowdsourcing Environment. ISPE CE,
Chang, D., & Lee, C. (2018). A product affective properties identification approach based on web mining in a crowdsourcing environment. Journal of Engineering Design, 29(8-9), 449-483.
Chiu, M.-C., & Lin, K.-Z. (2018). Utilizing text mining and Kansei Engineering to support data-driven design automation at conceptual design stage. Advanced Engineering Informatics, 38, 826-839.
Choudhary, A. K., Harding, J. A., & Tiwari, M. K. (2009). Data mining in manufacturing: a review based on the kind of knowledge. Journal of Intelligent Manufacturing, 20(5), 501.
Christensen, K., Nørskov, S., Frederiksen, L., & Scholderer, J. (2017). In search of new product ideas: Identifying ideas in online communities by machine learning and text mining. Creativity and Innovation Management, 26(1), 17-30.
Costa, J. M., Rozenfeld, H., Amaral, C. S. T., Marcacinit, R. M., & Rezende, S. O. (2013). Systematization of recurrent new product development management problems. Engineering Management Journal, 25(1), 19-34.
Danni CHANGa, D. L., & HANa, T. (2015). An Ontology-Based Product Affective Properties Identification Approach. Transdisciplinary Engineering: A Paradigm Shift, 977.
Diodato, V. P., & Gellatly, P. (2013). Dictionary of bibliometrics. Routledge.
Elezi, F., Sharafi, A., Mirson, A., Wolf, P., Krcmar, H., & Lindemann, U. (2011). A Knowledge Discovery in Databases (KDD) approach for extracting causes of iterations in Engineering Change Orders. ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference,
Feldman, R., & Sanger, J. (2007). The text mining handbook: advanced approaches in analyzing unstructured data. Cambridge university press.
Garfield, E. (1983). HOW TO USE JOURNAL-CITATION-REPORTS, INCLUDING A SPECIAL SALUTE TO THE JOHNS-HOPKINS-MEDICAL-JOURNAL. Current Contents(17), 5-12.
Giannakis, M., Dubey, R., Yan, S., Spanaki, K., & Papadopoulos, T. (2022). Social media and sensemaking patterns in new product development: demystifying the customer sentiment. Annals of Operations Research, 308, 145-175.
Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
Idrees, H., Xu, J., Haider, S. A., & Tehseen, S. (2023). A systematic review of knowledge management and new product development projects: Trends, issues, and challenges. Journal of Innovation & Knowledge, 8(2), 100350.
Ji, P., & Jin, J. (2015). Extraction of comparative opinionate sentences from product online reviews. 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD),
Jin, J., Ji, P., & Kwong, C. (2016). What makes consumers unsatisfied with your products: Review analysis at a fine-grained level. Engineering Applications of Artificial Intelligence, 47, 38-48.
Jin, J., Liu, Y., Ji, P., & Liu, H. (2016). Understanding big consumer opinion data for market-driven product design. International Journal of Production Research, 54(10), 3019-3041.
Joung, J., Jung, K., Ko, S., & Kim, K. (2019). Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development. Sustainability, 11(1), 40.
Kang, S. W., & Tucker, C. (2016). An automated approach to quantifying functional interactions by mining large-scale product specification data. Journal of Engineering Design, 27(1-3), 1-24.
Khriyenko, O. (2016). Customer Perception Driven Product Evolution: Facilitation of Structured Feedback Collection. WEBIST 2016: Proceedings of the 12th International conference on web information systems and technologies. Volume 2, ISBN 978-989-758-186-1,
Kim, H., Liu, Y., Wang, Y., & Wang, C. (2016). Data-Driven Design (D3). Journal of Mechanical Design, 138(12), 128002.
Kim, W., Ko, T., Rhiu, I., & Yun, M. H. (2019). Mining affective experience for a kansei design study on a recliner. Applied ergonomics, 74, 145-153.
Kuo-Yi, L. (2018). A TEXT MINING APPROACH TO CAPTURE USER EXPERIENCE FOR NEW PRODUCT DEVELOPMENT. International Journal of Industrial Engineering-Applications and Practice, 25(1).
Law, E. L.-C., Roto, V., Hassenzahl, M., Vermeeren, A. P., & Kort, J. (2009). Understanding, scoping and defining user experience: a survey approach. Proceedings of the SIGCHI conference on human factors in computing systems,
Lee, C., Song, B., & Park, Y. (2012). Design of convergent product concepts based on functionality: An association rule mining and decision tree approach. Expert Systems with Applications, 39(10), 9534-9542.
Lee, T. Y. (2009). Adaptive text extraction for new product development. ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference,
Lee, T. Y., & Bradlow, E. T. (2011). Automated marketing research using online customer reviews. Journal of Marketing Research, 48(5), 881-894.
Li, J., Lan, Q., Liu, L., & Yang, F. (2017). Consumer Stated Preference for Acer Laptop from Online Reviews. WHICEB,
Liang, Y., & Liu, Y. (2013). Rationale-based patent analysis for corporate product design. ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference,
Liang, Y., Liu, Y., Kwong, C. K., & Lee, W. B. (2012). Learning the “Whys”: Discovering design rationale using text mining—An algorithm perspective. Computer-Aided Design, 44(10), 916-930.
Liang, Y., Tan, R., & Ma, J. (2008). Patent analysis with text mining for TRIZ. 2008 4th IEEE International Conference on Management of Innovation and Technology,
Liang, Y., Tan, R., Wang, C., & Li, Z. (2009). Computer-aided classification of patents oriented to TRIZ. 2009 IEEE International Conference on Industrial Engineering and Engineering Management,
Lim, S., & Tucker, C. S. (2016). A bayesian sampling method for product feature extraction from large-scale textual data. Journal of Mechanical Design, 138(6), 061403.
Lin, C. J., & Cheng, L.-Y. (2017). Product attributes and user experience design: how to convey product information through user-centered service. Journal of Intelligent Manufacturing, 28(7), 1743-1754.
Lin, K.-Y. (2018). A TEXT MINING APPROACH TO CAPTURE USER EXPERIENCE FOR NEW PRODUCT DEVELOPMENT. International Journal of Industrial Engineering, 25(1).
Loh, H. T., Sun, J., Wang, J., & Lu, W. F. (2009). Opinion extraction from customer reviews. ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference,
Marques, C. A. N., Matsuno, I. P., Sinoara, R. A., Rezende, S. O., & Rozenfeld, H. (2015). An exploratory study to evaluate the practical application of PSS methods and tools based on text mining. DS 80-7 Proceedings of the 20th International Conference on Engineering Design (ICED 15) Vol 7: Product Modularisation, Product Architecture, systems Engineering, Product Service Systems, Milan, Italy, 27-30.07. 15,
Mashhadi, A. R., Esmaeilian, B., Cade, W., Wiens, K., & Behdad, S. (2016). Mining consumer experiences of repairing electronics: Product design insights and business lessons learned. Journal of Cleaner Production, 137, 716-727.
Mattsson, J., & Helmersson, H. (2007). Food product development: A consumer-led text analytic approach to generate preference structures. British Food Journal, 109(3), 246-259.
Osareh, F. (1996). Bibliometrics, citation analysis and co-citation analysis: A review of literature I. Libri, 46(3), 149-158.
Park, Y., & Lee, S. (2011). How to design and utilize online customer center to support new product concept generation. Expert Systems with Applications, 38(8), 10638-10647.
Petersen, K., Feldt, R., Mujtaba, S., & Mattsson, M. (2008). Systematic mapping studies in software engineering. Ease,
Potter, W. G. (1988). " Of Making Many Books There Is No End": Bibliometrics and Libraries. Journal of Academic Librarianship, 14(4), 238a-238c.
Rathore, A. K., & Ilavarasan, P. V. (2017). Social media analytics for new product development: Case of a pizza. 2017 International Conference on Advances in Mechanical, Industrial, Automation and Management Systems (AMIAMS),
Roy, U., Zhu, B., Li, Y., Zhang, H., & Yaman, O. (2014). Mining big data in manufacturing: requirement analysis, tools and techniques. ASME 2014 International Mechanical Engineering Congress and Exposition,
Seo, W., Yoon, J., Park, H., Coh, B.-y., Lee, J.-M., & Kwon, O.-J. (2016). Product opportunity identification based on internal capabilities using text mining and association rule mining. Technological Forecasting and Social Change, 105, 94-104.
Smith, L. C. (1981). Citation analysis.
Tao, X. T., Robson, P. J., & Wang, C. L. (2023). To learn or not to learn from new product development project failure: The roles of failure experience and error orientation. Technovation, 127, 102830.
Thorleuchter, D., Van den Poel, D., & Prinzie, A. (2010). Extracting consumers needs for new products-a web mining approach. 2010 Third International Conference on Knowledge Discovery and Data Mining,
Tuarob, S., Lim, S., & Tucker, C. S. (2018). Automated Discovery of Product Feature Inferences Within Large-Scale Implicit Social Media Data. Journal of Computing and Information Science in Engineering, 18(2), 021017.
Tucker, C., & Kim, H. (2011). Predicting emerging product design trend by mining publicly available customer review data. DS 68-6: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society through Engineering Design, Vol. 6: Design Information and Knowledge, Lyngby/Copenhagen, Denmark, 15.-19.08. 2011,
Uhm, D., Ryu, J.-B., & Jun, S. (2017). An Interval Estimation Method of Patent Keyword Data for Sustainable Technology Forecasting. Sustainability, 9(11), 2025.
Wang, W., Li, Z., Liu, L., Tian, Z., & Tsui, E. (2018). Mining of affective responses and affective intentions of products from unstructured text. Journal of Engineering Design, 29(7), 404-429.
Wang, W., Li, Z., Tian, Z., Wang, J., & Cheng, M. (2018). Extracting and summarizing affective features and responses from online product descriptions and reviews: A Kansei text mining approach. Engineering Applications of Artificial Intelligence, 73, 149-162.
Wei, C.-P., Yang, C.-S., & Huang, C.-N. (2006). Turning online product reviews to customer knowledge: A semantic-based sentiment classification approach. PACIS 2006 Proceedings, 50.
Yang, B., Liu, Y., Liang, Y., & Tang, M. (2019). Exploiting user experience from online customer reviews for product design. International Journal of Information Management, 46, 173-186.
Yoon, J., Seo, W., Coh, B.-Y., Song, I., & Lee, J.-M. (2017). Identifying product opportunities using collaborative filtering-based patent analysis. Computers & Industrial Engineering, 107, 376-387.