Group decision-making processes can be supported by group recommender systems that
help groups of users obtain satisfying decision outcomes. These systems integrate a …

User preferences are a crucial input needed by recommender systems to determine relevant
items. In single-shot recommendation scenarios such as content-based filtering and …

Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …

Psychological factors such as personality, emotions, social connections, and decision
biases can significantly affect the outcome of a decision process. These factors are also …

Recommender systems are software applications that make tailored item suggestions to
users, usually with the goal of hel** them overcome information overload or make …

Small group researchers are increasingly called to engage the computational sciences. One
challenge in answering this call is the lack of information concerning what the study of small …

Primacy/recency effects, also known as serial position effects, are cognitive biases triggered
when items are presented in the form of a list. Affected by these effects, users tend to recall …

Decision biases can be interpreted as tendencies to think and act in specific ways that result
in a systematic deviation of potentially rational and high-quality decisions. In this chapter, we …

Serial position effects are triggered in recommendation scenarios where users focus on
evaluating items shown at the beginning and at the end of a list. In this paper, we analyze …

The information cluster that supports the final decision in a decision task is usually
presented as a series of information. According to the serial position effect, the decision …