An Adaptive Contextual Recommender System: a Slow Intelligence Perspective

Colace, Francesco; Greco, Luca; Lemma, Saverio; Lombardi, Marco; Yung, Duncan; Chang, Shi

doi:10.18293/seke2015-080

Cited by 12 publications

(7 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In a recommender system, the use of hierarchies allows for the representation of the user’s context and the item’s context. This representation enables an easy understanding and a match among hierarchies [ 4 , 6 ]. These hierarchies can be built manually or dynamically [ 14 ].…”

Section: Recommender Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Recommendation of Workplaces in a Coworking Building: A Cyber-Physical Approach Supported by a Context-Aware Multi-Agent System

Gomes

Almeida

Vale

2020

Sensors

View full text Add to dashboard Cite

Recommender systems are able to suggest the most suitable items to a given user, taking into account the user’s and item`s data. Currently, these systems are offered almost everywhere in the online world, such as in e-commerce websites, newsletters, or video platforms. To improve recommendations, the user’s context should be considered to provide more accurate algorithms able to achieve higher payoffs. In this paper, we propose a pre-filtering recommendation system that considers the context of a coworking building and suggests the best workplaces to a user. A cyber-physical context-aware multi-agent system is used to monitor the building and feed the pre-filtering process using fuzzy logic. Recommendations are made by a multi-armed bandit algorithm, using ϵ -greedy and upper confidence bound methods. The paper presents the main results of simulations for one, two, three, and five years to illustrate the use of the proposed system.

show abstract

Section: Recommender Systemsmentioning

confidence: 99%

“…The algorithms that they use can engage the user and increase user experience. Another promising application area where contextual recommender systems are getting applied is tourism [ 4 , 5 , 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

Recommendation of Workplaces in a Coworking Building: A Cyber-Physical Approach Supported by a Context-Aware Multi-Agent System

Gomes

Almeida

Vale

2020

Sensors

View full text Add to dashboard Cite

show abstract

“…Therefore, with the increasing availability of user-generated content, thanks to consumer opinion websites, social networks, blogs, forums, users have opportunities to express opinions and make them available to everyone. In this sense, a new collective intelligence is arisen and can be used as source of valuable information for the decision-making processes [1], [2], [3]. This is nothing new: the preparatory process for a choice has always been characterized by the search for information that could support it.…”

Section: Introductionmentioning

confidence: 99%

Sentiment Analysis in Social Networks: A Methodology Based on the Latent Dirichlet Allocation Approach

Santaniello

Colace

Lombardi

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

Self Cite

View full text Add to dashboard Cite

The detection and analysis of sentiment in textual communication is a topic attracting attention in both academia and industry. In fact, thanks to the explosion of the Social Networks a wealth of information is produced every day. This huge amount of contents can be very helpful in assessing the general public's sentiment and opinions toward products, services and topics. This paper presents a methodology for the detection of sentiment in textual contents using a methodology based on the Latent Dirichlet Allocation (LDA) approach and a word-based graphical model, the mixed graph of terms. The method has been tested in various operative scenarios: on standard datasets, on datasets obtained collecting tweets from twitter and on datasets coming from social networks as Twitter and TripAdvisor. The experimental campaigns show that the proposed approach is effective and furnishes good and reliable results in each context.

show abstract

“…Eventually, the cloud computing technologies provide a natural infrastructure to support smart services [4].…”

Section: Introductionmentioning

confidence: 99%

A Context-Aware Mobile Solution for Assisting Tourists in a Smart Environment

Colace¹,

Lemma²,

Lombardi³

et al. 2017

Proceedings of the 50th Hawaii International Conference on System Sciences (2017)

Self Cite

View full text Add to dashboard Cite

show abstract

An Adaptive Contextual Recommender System: a Slow Intelligence Perspective

Cited by 12 publications

References 36 publications

Recommendation of Workplaces in a Coworking Building: A Cyber-Physical Approach Supported by a Context-Aware Multi-Agent System

Recommendation of Workplaces in a Coworking Building: A Cyber-Physical Approach Supported by a Context-Aware Multi-Agent System

Sentiment Analysis in Social Networks: A Methodology Based on the Latent Dirichlet Allocation Approach

A Context-Aware Mobile Solution for Assisting Tourists in a Smart Environment

Contact Info

Product

Resources

About