Recent research and developments in the field of Sentiment Analysis (SA) have made it
possible to simplify the detection and classification of sentiments from the textual content …

The social network-based recommendation algorithm can not only effectively solve the
information overload problem, but also fully exploit the personalized preferences of users …

Massive open online courses (MOOC) are free learning courses based on online platforms
for higher education, which not only promote the open sharing of learning resources, but …

In the face of problems such as information overload and the information cocoon resulting
from big data, it is a key point of current research to solve the problem of semantic fuzziness …

This study employs a novel fuzzy logic-based framework to address multi-attribute group
decision-making problems commonly encountered in modern astronomy. Our approach …

Collaborative filtering (CF) is the most popular approach for predicting relevant items in
recommender systems. However, basic CF suffers from some serious problems including …

Collective tourist destination recommendation refers to recommending tourist attractions to
groups, which not only satisfies the diverse demands of consumers but also generates …

The current employment environment is becoming increasingly complex, with many job
seekers competing with each other in more concentrated and narrower fields, worsening the …

In dieser Bachelorarbeit wurde erforscht, wie Vertrauen und wahrgenommenes
Greenwashing durch die Vertrauensdeterminanten Integrität, Interessen, Fähigkeit, und …

Personalized recommendation systems fundamentally assess user preferences as a
reflection of their emotional responses to items. Traditional recommendation algorithms …