Ten years of sentic computing
Sentic computing is a multi-disciplinary approach to sentiment analysis at the crossroads
between affective computing and commonsense computing, which exploits both computer …
between affective computing and commonsense computing, which exploits both computer …
[HTML][HTML] Disruptive technologies for parliaments: A literature review
Exploitation and use of disruptive technologies, such as the Internet of Things, recommender
systems, and artificial intelligence, with an ambidextrous balance, are a challenge …
systems, and artificial intelligence, with an ambidextrous balance, are a challenge …
[HTML][HTML] Using topic models with browsing history in hybrid collaborative filtering recommender system: Experiments with user ratings
DPD Rajendran, RP Sundarraj - International Journal of Information …, 2021 - Elsevier
Personalizing user experience in recommender systems is possible when there is sufficient
information about the user. But when new users join the system, the unavailability of …
information about the user. But when new users join the system, the unavailability of …
Do psychological attributes of online review play role in predicting rating? An empirical investigation
Rating provided by online customers is a process to summarize quality of the product
consumed. Extant research on review rating prediction primarily considered the task as …
consumed. Extant research on review rating prediction primarily considered the task as …
Investigating the impact of recommender systems on user-based and item-based popularity bias
Recommender Systems are decision support tools that adopt advanced algorithms in order
to help users to find less-explored items that can be interesting for them. While …
to help users to find less-explored items that can be interesting for them. While …
RDERL: Reliable deep ensemble reinforcement learning-based recommender system
Recommender systems (RSs) have been employed for many real-world applications
including search engines, social networks, and information retrieval systems as powerful …
including search engines, social networks, and information retrieval systems as powerful …
[HTML][HTML] Data-assisted persona construction using social media data
User experience design and subsequent usability evaluation can benefit from knowledge
about user interaction, types, deployment settings and situations. Most of the time, the user …
about user interaction, types, deployment settings and situations. Most of the time, the user …
Providing reliability in recommender systems through Bernoulli matrix factorization
Beyond accuracy, quality measures are gaining importance in modern recommender
systems, with reliability being one of the most important indicators in the context of …
systems, with reliability being one of the most important indicators in the context of …
Combining rating and review data by initializing latent factor models with topic models for top-n recommendation
Nowadays we commonly have multiple sources of data associated with items. Users may
provide numerical ratings, or implicit interactions, but may also provide textual reviews …
provide numerical ratings, or implicit interactions, but may also provide textual reviews …
[HTML][HTML] Cross-platform hotel evaluation by aggregating multi-website consumer reviews with probabilistic linguistic term set and Choquet integral
In order to adequately utilize and integrate both ratings and comments from multiple
websites, this paper proposes a new hotel evaluation model with probabilistic linguistic …
websites, this paper proposes a new hotel evaluation model with probabilistic linguistic …