Creating top ranking options in the continuous option and preference space

Bo Tang, Kyriakos Mouratidis, Man Lung Yiu, Zhenyu Chen

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Top-k queries are extensively used to retrieve the k most relevant options (e.g., products, services, accommodation alternatives, etc) based on a weighted scoring function that captures user preferences. In this paper, we take the viewpoint of a business owner who plans to introduce a new option to the market, with a certain type of clientele in mind. Given a target region in the consumer spectrum, we determine what attribute values the new option should have, so that it ranks among the top-k for any user in that region. Our methodology can also be used to improve an existing option, at the minimum modification cost, so that it ranks consistently high for an intended type of customers. This is the first work on competitive option placement where no distinct user(s) are targeted, but a general clientele type, i.e., a continuum of possible preferences. Here also lies our main challenge (and contribution), i.e., dealing with the interplay between two continuous spaces: the targeted region in the preference spectrum, and the option domain (where the new option will be placed). At the core of our methodology lies a novel and powerful interlinking between the two spaces. Our algorithms offer exact answers in practical response times, even for the largest of the standard benchmark datasets.
Original languageEnglish
Title of host publicationProceedings of the VLDB Endowment
Number of pages14
Publication statusPublished - Jun 2019
Event45th International Conference on Very Large Data Bases, VLDB 2019 - Los Angeles, United States
Duration: 26 Aug 201930 Aug 2019

Publication series

NameProceedings of the VLDB Endowment
ISSN (Electronic)2150-8097


Conference45th International Conference on Very Large Data Bases, VLDB 2019
Country/TerritoryUnited States
CityLos Angeles


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