5 citations · 6 across the 6 of their papers we have counts for
7 papers
How Researchers Could Obtain Quick and Cheap User Feedback on their Algorithms Without Having to Operate their Own Recommender System
Tobias Eichinger, Ananta Lamichhane
The majority of recommendation algorithms are evaluated on the basis of historic benchmark datasets. Evaluation on historic benchmark datasets is quick and cheap to conduct, yet ex…
Can We Effectively Use Smart Contracts to Stipulate Time Constraints?
Tobias Eichinger, Marcel Ebermann
Smart contracts provide the means to stipulate rules of interaction between mutually distrustful organizations. They encode contractual agreements on the basis of source code, whic…
On Gossip-based Information Dissemination in Pervasive Recommender Systems
Tobias Eichinger, Felix Beierle, Robin Papke +3
Pervasive computing systems employ distributed and embedded devices in order to raise, communicate, and process data in an anytime-anywhere fashion. Certainly, its most prominent d…
Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems
Felix Beierle, Tobias Eichinger
Typically, recommender systems from any domain, be it movies, music, restaurants, etc., are organized in a centralized fashion. The service provider holds all the data, biases in t…
affinity: A System for Latent User Similarity Comparison on Texting Data
Tobias Eichinger, Felix Beierle, Sumsam Ullah Khan +3
In the field of social networking services, finding similar users based on profile data is common practice. Smartphones harbor sensor and personal context data that can be used for…
The Corpus Replication Task
Tobias Eichinger
In the field of Natural Language Processing (NLP), we revisit the well-known word embedding algorithm word2vec. Word embeddings identify words by vectors such that the words' distr…