Instant Foodie: Predicting Expert Ratings From Grassroots
Venue
CIKM’13, Oct. 27–Nov. 1, 2013, San Francisco, CA, USA, ACM
Publication Year
2013
Authors
Chenhao Tan, Ed H. Chi, David Huffaker, Gueorgi Kossinets, Alex J. Smola
BibTeX
Abstract
Consumer review sites and recommender systems typically rely on a large volume of
user-contributed ratings, which makes rating acquisition an essential component in
the design of such systems. User ratings are then summarized to provide an
aggregate score representing a popular evaluation of an item. An inherent problem
in such summarization is potential bias due to raters’ self-selection and
heterogeneity in terms of experiences, tastes and rating scale interpretations.
There are two major approaches to collecting ratings, which have different
advantages and disadvantages. One is to allow a large number of volunteers to
choose and rate items directly (a method employed by e.g. Yelp and Google Places).
Alternatively, a panel of raters may be maintained and invited to rate a predefined
set of items at regular intervals (such as in Zagat Survey). The latter approach
arguably results in more consistent reviews and reduced selection bias, however, at
the expense of much smaller coverage (fewer rated items). In this paper, we examine
the two different approaches to collecting user ratings of restaurants and explore
the question of whether it is possible to reconcile them. Specifically, we study the
problem of inferring the more calibrated Zagat Survey ratings (which we dub “expert
ratings”) from the user-contributed ratings (“grassroots”) in Google Places. To
achieve this, we employ latent factor models and provide a probabilistic treatment
of the ordinal ratings. We can predict Zagat Survey ratings accurately from ad hoc
user-generated ratings by employing joint optimization. Furthermore, the resulting
model show that users become more discerning as they submit more ratings. We also
describe an approach towards cross-city recommendations, answering questions such
as “What is the equivalent of the Per Se restaurant in Chicago?”
