Association Rules for Recommendations with Multiple Items
Published Online:6 Mar 2014https://doi.org/10.1287/ijoc.2013.0575
References
- (2007) Validation sequence optimization: A theoretical approach. INFORMS J. Comput. 19(2):185–200.Link, Google Scholar
- (1993) Mining association rules between sets of items in large databases. Proc. ACM SIGMOD Conf. Management of Data, Washington, DC, 207–216.Crossref, Google Scholar
- (1999) The use of association rules for product assortment decisions: A case study. Proc. Fifth ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining, San Diego.Crossref, Google Scholar
- (2007) Google news personalization: Scalable online collaborative filtering. Proc. 16th Internat. World Wide Web Conf., Banff, Alberta, Canada, 271–280.Crossref, Google Scholar
- (2011) How to increase your conversion rate with personalization and discovery. Boosting Ecommerce (November 10), http://www.boostingecommerce.com/how-to-increase-your-conversion-rate-with-personalization-and-discovery.Google Scholar
- (2003) Enhancing the web customer's experience: Techniques and business impacts of web personalization and customization. Proc. Inform. Systems Ed. Conf., San Diego.Google Scholar
- (2009) Massive—An intelligent shopping assistant. Proc. Workshop Personalization Mobile Pervasive Comput., Trento, Italy.Google Scholar
- (2006) Netflix update: Try this at home. Accessed January 12, 2013, http://sifter.org/∼simon/journal/20061211.html.Google Scholar
- (2008) Leading practices in market basket analysis. How top retailers are using market basket analysis to win margin and market share. Factpoint Group. Accessed March 11, 2012, http://factpoint.com/pdf2/1.pdf.Google Scholar
- (2004) Mining frequent patterns without candidate generation: A frequent-pattern tree approach. Data Mining Knowledge Discovery 8:53–87.Crossref, Google Scholar
- (2000) Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Sci. 19(1):4–21.Link, Google Scholar
- IBM (2009a) IBM SPSS retail market basket analysis. Accessed April 11, 2012, ftp://service.boulder.ibm.com/software/uk/data/ibm-spss-retail-datasheet.pdf.Google Scholar
- IBM (2009b, 2012) Retail market basket analysis. Accessed April 11, 2012, https://www-304.ibm.com/easyaccess/fileserve/?contentid=193973.Google Scholar
- (2012) Standard metrics revisited: 3: Bounce rate. Accessed March 11, 2012, http://www.kaushik.net/avinash/standard-metrics-revisited-3-bounce-rate/.Google Scholar
- (2003) A recommendation algorithm using multi-level association rules. IEEE/WIC Internat. Conf. Web Intelligence (WI'03), Halifax, Canada.Google Scholar
- (2009) Beyond the grocery and retail store: Applying market basket analysis to the service industry. A 1010Data White Paper. Accessed March 11, 2012, http://www.1010data.com/downloads/mba-service-industry.pdf.Google Scholar
- (2002) Mining optimized association rules with categorical and numeric attributes. IEEE Trans. Knowledge Data Engrg. 14(1):29–50.Crossref, Google Scholar
- (2001) The personalization story. IT World.com (November 5), http://www.itworld.com/ITW010511rosenberg.Google Scholar
- (2003) Web personalization: Is it effective? IT Professional 5(5):53–57.Crossref, Google Scholar
- (2008) If you liked this, you're sure to love that. The New York Times Magazine (November 21), http://www.nytimes.com/2008/11/23/magazine/23Netflix-t.html?pagewanted=all&_r=0.Google Scholar
- (2008) Data Warehousing and Mining: Concepts, Methodologies, Tools and Applications, 1st ed. (Information Science Reference, New York).Crossref, Google Scholar
- (2004) Effective personalized recommendation based on time-framed navigation clustering and association mining. Expert Systems Appl. 27(3):365–377.Crossref, Google Scholar
- (2002) Building a recommender agent for e-learning systems. Proc. Internat. Conf. Comput. Ed., Washington, DC.Crossref, Google Scholar

