TY - GEN
T1 - Extracting and ranking travel tips from user-generated reviews
AU - Guy, Ido
AU - Nus, Alexander
AU - Mejer, Avihai
AU - Raiber, Fiana
N1 - Publisher Copyright:
© 2017 International World Wide Web Conference Committee (IW3C2)
PY - 2017/1/1
Y1 - 2017/1/1
N2 - User-generated reviews are a key driving force behind some of the leading websites, such as Amazon, TripAdvisor, and Yelp. Yet, the proliferation of user reviews in such sites also poses an information overload challenge: many items, especially popular ones, have a large number of reviews, which cannot all be read by the user. In this work, we propose to extract short practical tips from user reviews. We focus on tips for travel attractions extracted from user reviews on TripAdvisor. Our method infers a list of templates from a small gold set of tips and applies them to user reviews to extract tip candidates. For each attraction, the associated candidates are then ranked according to their predicted usefulness. Evaluation based on labeling by professional annotators shows that our method produces high-quality tips, with good coverage of cities and attractions.
AB - User-generated reviews are a key driving force behind some of the leading websites, such as Amazon, TripAdvisor, and Yelp. Yet, the proliferation of user reviews in such sites also poses an information overload challenge: many items, especially popular ones, have a large number of reviews, which cannot all be read by the user. In this work, we propose to extract short practical tips from user reviews. We focus on tips for travel attractions extracted from user reviews on TripAdvisor. Our method infers a list of templates from a small gold set of tips and applies them to user reviews to extract tip candidates. For each attraction, the associated candidates are then ranked according to their predicted usefulness. Evaluation based on labeling by professional annotators shows that our method produces high-quality tips, with good coverage of cities and attractions.
UR - http://www.scopus.com/inward/record.url?scp=85029387228&partnerID=8YFLogxK
U2 - 10.1145/3038912.3052632
DO - 10.1145/3038912.3052632
M3 - Conference contribution
AN - SCOPUS:85029387228
SN - 9781450349130
T3 - 26th International World Wide Web Conference, WWW 2017
SP - 987
EP - 996
BT - 26th International World Wide Web Conference, WWW 2017
PB - International World Wide Web Conferences Steering Committee
T2 - 26th International World Wide Web Conference, WWW 2017
Y2 - 3 April 2017 through 7 April 2017
ER -