Quantifying the competitiveness of a dataset in relation to general preferences

Mouratidis，Kyriakos1; Li，Keming2; Tang，Bo3

2023

10.1007/s00778-023-00804-1

VLDB Journal   Impact Factor & Quartile

1066-8888

0949-877X

Typically, a specific market (e.g., of hotels, restaurants, laptops, etc.) is represented as a multi-attribute dataset of the available products. The topic of identifying and shortlisting the products of most interest to a user has been well-explored. In contrast, in this work we focus on the dataset, and aim to assess its competitiveness with regard to different possible preferences. We define measures of competitiveness, and represent them in the form of a heat-map in the domain of preferences. Our work finds application in market analysis and in business development. These applications are further enhanced when the competitiveness heat-map is used in tandem with information on user preferences (which can be readily derived by existing methods). Interestingly, our study also finds side-applications with strong practical relevance in the area of multi-objective querying. We propose a suite of algorithms to efficiently produce the heat-map, and conduct case studies and an empirical evaluation to demonstrate the practicality of our work.

Heat-map Market analysis Multi-dimensional data Preference queries

SCI

English

Others

Ministry of Education, Singapore, under its Academic Research Fund Tier 2[MOE-T2EP20121-0002] ; Shenzhen Fundamental Research Program[20220815112848002]

Computer Science

Computer Science, Hardware & Architecture ; Computer Science, Information Systems

WOS:001044321500001

SPRINGER

COMPUTER SCIENCE

2-s2.0-85167356360

Scopus

1.School of Computing and Information Systems,Singapore Management University,Singapore,Singapore
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China
3.Research Institute of Trustworthy Autonomous Systems,Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China

Mouratidis，Kyriakos,Li，Keming,Tang，Bo. Quantifying the competitiveness of a dataset in relation to general preferences[J]. VLDB Journal,2023.

Mouratidis，Kyriakos,Li，Keming,&Tang，Bo.(2023).Quantifying the competitiveness of a dataset in relation to general preferences.VLDB Journal.

Mouratidis，Kyriakos,et al."Quantifying the competitiveness of a dataset in relation to general preferences".VLDB Journal (2023).