Toward the next generation of news recommender systems
Edward C. Malthouse1
1
    Northwestern University, Illinois, United States


                                             Abstract
                                             This talk will discuss the complexities of designing news recommender system (RS) outputs such as newsletters and websites.
                                             There will be two main parts to the talk: (1) designing news RS outputs to balance between short- and longer-term objectives;
                                             and (2) creating bundled recommendations with the table d’hote (“host’s table”) approach. First, RS often optimize short-
                                             term metrics that can be easily measured, but the strategic business goals of the system are typically realized over a longer
                                             period of time and are more difficult to measure, e.g., customer lifetime value (CLV), which is the discount sum of expected
                                             future cash flows due to the relationship. I will give empirical examples showing how optimizing some short-term news
                                             goals can harm the long-term goal. This hazard can be avoided by proposing and testing a causal model linking the short-
                                             and long-term goals through mediators. In the case of news RS, the key mediator is engagement, which is how news outputs
                                             create value for readers. I will establish short-term engagement metrics. The second part describes the table d’hote approach
                                             to create engaging RS outputs such as newsletters, which is motivated by the task of creating other “bundles” such as fine-
                                             dining experiences, musical concert set lists and art museum special exhibits. In all of these situations, the sequencing of
                                             items is an important consideration beyond more traditional RS goals such as coverage, novelty, diversity and serendipity.
                                             Table d’hote builds on communication theories and stratified sampling to create automated bundled news recommendations.
                                             It includes a typology of how news creates value for readers through different surveillance and serendipity experiences. I
                                             will discuss challenges for future research.

                                             Keywords
                                             Complex inputs, Complex output



1. Speaker
Edward C. Malthouse is the Erastus Otis Haven Professor
at Northwestern University and a research fellow at
the Media Management Center, a partnership between
Medill and Kellogg. He is also the research director of
the Medill IMC Spiegel Research Center.

   His research interests center on media marketing,
database marketing, advertising, new media and inte-
grated marketing communications. He develops statis-
tical models and applies them to large data sets of con-
sumer information to help managers make marketing
decisions. Malthouse is also currently the co-editor of
“Medill on Media Engagement.” He was the co-editor of
the Journal of Interactive Marketing from 2005-2011. His
professional experience includes software engineering
for AT&T Laboratories, corporate analytics training for
Accenture, BNSF, Digitas, Nuoqi and Capital One, and
developing segmentations for Cohorts and Financial Co-
horts and Motorola.




3rd Edition of Knowledge-aware and Conversational Recommender
Systems (KaRS) & 5th Edition of Recommendation in Complex
Environments (ComplexRec) Joint Workshop co-located with the 15th
ACM Conference on Recommender Systems (RecSys 2021)
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                  ISSN 1613-0073       CEUR Workshop Proceedings (CEUR-WS.org)