Understanding the Influence of Data Characteristics on the Performance of Point-of-Interest Recommendation Algorithms

no code implementations • 13 Nov 2023 • Linus W. Dietz, Pablo Sánchez, Alejandro Bellogín

The performance of recommendation algorithms is closely tied to key characteristics of the data sets they use, such as sparsity, popularity bias, and preference distributions.

Analyzing 'Near Me' Services: Potential for Exposure Bias in Location-based Retrieval

no code implementations • 14 Nov 2020 • Ashmi Banerjee, Gourab K Patro, Linus W. Dietz, Abhijnan Chakraborty

Online platforms like Google and Yelp allow location-based search in the form of nearby feature to query for hotels or restaurants in the vicinity.

Attribute Recommendation Systems +1

A Model for Using Physiological Conditions for Proactive Tourist Recommendations

no code implementations • 10 Apr 2019 • Rinita Roy, Linus W. Dietz

Mobile proactive tourist recommender systems can support tourists by recommending the best choice depending on different contexts related to herself and the environment.

Recommendation Systems

Online Evaluations for Everyone: Mr. DLib's Living Lab for Scholarly Recommendations

no code implementations • 19 Jul 2018 • Joeran Beel, Andrew Collins, Oliver Kopp, Linus W. Dietz, Petr Knoth

We present the architecture of Mr. DLib's living lab as well as usage statistics on the first sixteen months of operating it.

Management Recommendation Systems