IDEAS home Printed from https://ideas.repec.org/p/ems/eureri/15142.html
   My bibliography  Save this paper

Map Based Visualization of Product Catalogs

Author

Listed:
  • Kagie, M.
  • van Wezel, M.C.
  • Groenen, P.J.F.

Abstract

Traditionally, recommender systems present recommendations in lists to the user. In content- and knowledge-based recommendation systems these list are often sorted on some notion of similarity with a query, ideal product specification, or sample product. However, a lot of information is lost in this way, since two even similar products can differ from the query on a completely different set of product characteristics. When using a two dimensional, that is, a map-based, representation of the recommendations, it is possible to retain this information. In the map we can then position recommendations that are similar to each other in the same area of the map. Both in science and industry an increasing number of two dimensional graphical interfaces have been introduced over the last years. However, some of them lack a sound scientific foundation, while other approaches are not applicable in a recommendation setting. In our chapter, we will describe a framework, which has a solid scientific foundation (using state-of-the-art statistical models) and is specifically designed to work with e-commerce product catalogs. Basis of the framework is the Product Catalog Map interface based on multidimensional scaling. Also, we show another type of interface based on nonlinear principal components analysis, which provides an easy way in constraining the space based on specific characteristic values. Then, we discuss some advanced issues. Firstly, we discuss how the product catalog interface can be adapted to better fit the users' notion of importance of attributes using click stream analysis. Secondly, we show an user interface that combines recommendation by proposing with the map based approach. Finally, we show how these methods can be applied to a real e-commerce product catalog of MP3-players.

Suggested Citation

  • Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Map Based Visualization of Product Catalogs," ERIM Report Series Research in Management ERS-2009-010-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:15142
    as

    Download full text from publisher

    File URL: https://repub.eur.nl/pub/15142/ERS-2009-010-MKT.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2007. "A graphical shopping interface bases on product attributes," Econometric Institute Research Papers EI 2007-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Joseph G. Ibrahim & Ming-Hui Chen & Stuart R. Lipsitz & Amy H. Herring, 2005. "Missing-Data Methods for Generalized Linear Models: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 332-346, March.
    3. Hsinchun Chen & Andrea L. Houston & Robin R. Sewell & Bruce R. Schatz, 1998. "Internet browsing and searching: User evaluations of category map and concept space techniques," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 49(7), pages 582-603, May.
    4. Jan Leeuw, 1977. "Correctness of Kruskal's algorithms for monotone regression with ties," Psychometrika, Springer;The Psychometric Society, vol. 42(1), pages 141-144, March.
    5. Bert Green, 1952. "The orthogonal approximation of an oblique structure in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 429-440, December.
    6. King, Gary & Honaker, James & Joseph, Anne & Scheve, Kenneth, 2001. "Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation," American Political Science Review, Cambridge University Press, vol. 95(1), pages 49-69, March.
    7. John D. Black & A. F. Hinrichs & A. Kaiming Chiu & Kurt Schneider & J. Clyde Marquis & Walter J. Roth, 1929. "Notes," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 11(4), pages 643-663.
    8. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    9. Warren Torgerson, 1952. "Multidimensional scaling: I. Theory and method," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 401-419, December.
    10. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2008. "Choosing Attribute Weights for Item Dissimilarity using Clikstream Data with an Application to a Product Catalog Map," ERIM Report Series Research in Management ERS-2008-024-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. Jan Leeuw, 1988. "Convergence of the majorization method for multidimensional scaling," Journal of Classification, Springer;The Classification Society, vol. 5(2), pages 163-180, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Borg, I. & Groenen, P.J.F. & Jehn, K.A. & Bilsky, W. & Schwartz, S.H., 2009. "Embedding the Organizational Culture Profile into Schwartz’s Universal Value Theory using Multidimensional Scaling with Regional Restrictions," ERIM Report Series Research in Management ERS-2009-017-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "Determination of Attribute Weights for Recommender Systems Based on Product Popularity," ERIM Report Series Research in Management ERS-2009-022-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    2. Herden, Gerhard & Pallack, Andreas, 2005. "Adequateness and interpretability of objective functions in ordinal data analysis," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 19-69, May.
    3. Leung, Pui Lam & Lau, Kin-nam, 2004. "Estimating the city-block two-dimensional scaling model with simulated annealing," European Journal of Operational Research, Elsevier, vol. 158(2), pages 518-524, October.
    4. Gruenhage, Gina & Opper, Manfred & Barthelme, Simon, 2016. "Visualizing the effects of a changing distance on data using continuous embeddings," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 51-65.
    5. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2009. "An Empirical Comparison of Dissimilarity Measures for Recommender Systems," ERIM Report Series Research in Management ERS-2009-023-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Venera Tomaselli, 1996. "Multivariate statistical techniques and sociological research," Quality & Quantity: International Journal of Methodology, Springer, vol. 30(3), pages 253-276, August.
    7. Bijmolt, T.H.A. & Wedel, M., 1996. "A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods," Other publications TiSEM f72cc9d8-f370-43aa-a224-4, Tilburg University, School of Economics and Management.
    8. Morales José F. & Song Tingting & Auerbach Arleen D. & Wittkowski Knut M., 2008. "Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-20, June.
    9. Hansohm, Jürgen, 2007. "Algorithms and error estimations for monotone regression on partially preordered sets," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1043-1050, May.
    10. Kagie, M. & van Wezel, M.C. & Groenen, P.J.F., 2007. "A graphical shopping interface bases on product attributes," Econometric Institute Research Papers EI 2007-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Bijmolt, T.H.A. & Wedel, M., 1996. "A Monte Carlo Evaluation of Maximum Likelihood Multidimensional Scaling Methods," Research Memorandum 725, Tilburg University, School of Economics and Management.
    12. Cristian Rizzo & Matteo Di Giuseppe & Domenico Moramarco & Simone Pizzi & Myriam Portaluri & Gianluigi Guido, 2016. "L?effetto dell?inquinamento acustico sulla distanza percepita dei punti vendita," ESPERIENZE D'IMPRESA, FrancoAngeli Editore, vol. 2016(1), pages 65-79.
    13. Xiaomeng Cao & Yuan Gao & Jingwei Cui & Shuangbiao Han & Lei Kang & Sha Song & Chengshan Wang, 2020. "Pore Characteristics of Lacustrine Shale Oil Reservoir in the Cretaceous Qingshankou Formation of the Songliao Basin, NE China," Energies, MDPI, vol. 13(8), pages 1-25, April.
    14. He, Jiayi & Shang, Pengjian & Xiong, Hui, 2018. "Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 210-221.
    15. Si-Tong Lu & Miao Zhang & Qing-Na Li, 2020. "Feasibility and a fast algorithm for Euclidean distance matrix optimization with ordinal constraints," Computational Optimization and Applications, Springer, vol. 76(2), pages 535-569, June.
    16. Lin, L. & Fong, D.K.H., 2019. "Bayesian multidimensional scaling procedure with variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 129(C), pages 1-13.
    17. Simon Grund & Oliver Lüdtke & Alexander Robitzsch, 2021. "On the Treatment of Missing Data in Background Questionnaires in Educational Large-Scale Assessments: An Evaluation of Different Procedures," Journal of Educational and Behavioral Statistics, , vol. 46(4), pages 430-465, August.
    18. W. J. Krzanowski, 2006. "Sensitivity in Metric Scaling and Analysis of Distance," Biometrics, The International Biometric Society, vol. 62(1), pages 239-244, March.
    19. Wayne DeSarbo & Joonwook Park & Crystal Scott, 2008. "A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 1-20, March.
    20. Flora Josiane Chadare & Nadia Fanou Fogny & Yann Eméric Madode & Juvencio Odilon G. Ayosso & Sèwanou Hermann Honfo & Folachodé Pierre Polycarpe Kayodé & Anita Rachel Linnemann & Djidjoho Joseph Hounho, 2018. "Local agro-ecological condition-based food resources to promote infant food security: a case study from Benin," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(4), pages 1013-1031, August.

    More about this item

    Keywords

    dissimilarity measure; map-based interface; multidimensional scaling; nonlinear principal components analysis; recommender systems;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ems:eureri:15142. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: RePub (email available below). General contact details of provider: https://edirc.repec.org/data/erimanl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.