Integrating Collaboration and Leadership in Conversational Group Recommender Systems

2021 ◽  
Vol 39 (4) ◽  
pp. 1-32
Author(s):  
David Contreras ◽  
Maria Salamó ◽  
Ludovico Boratto
Keyword(s):  
Social Interactions ◽  
Recommender System ◽  
Observational Studies ◽  
User Evaluation ◽  
Group Recommendation ◽  
Collaborative Model ◽  
Web Based ◽  
Group Recommender Systems ◽  
The Social ◽  
Group Recommender

Recent observational studies highlight the importance of considering the interactions between users in the group recommendation process, but to date their integration has been marginal. In this article, we propose a collaborative model based on the social interactions that take place in a web-based conversational group recommender system. The collaborative model allows the group recommender to implicitly infer the different roles within the group, namely, collaborative and leader user(s). Moreover, it serves as the basis of several novel collaboration-based consensus strategies that integrate both individual and social interactions in the group recommendation process. A live-user evaluation confirms that our approach accurately identifies the collaborative and leader users in a group and produces more effective recommendations.

Group Recommender Systems – An Evolutionary Approach Based on Multi-expert System for Consensus

2018 ◽  
Vol 29 (1) ◽  
pp. 1092-1108 ◽  
Author(s):  
Ritu Meena ◽  
Sonajharia Minz
Keyword(s):  
Recommender Systems ◽  
Group Recommendation ◽  
Group Recommender Systems ◽  
Maximum Utility ◽  
Group Members ◽  
Two Phases ◽  
The Individual ◽  
Multiple Experts ◽  
Group Profile ◽  
Group Recommender

Abstract Recommender systems have focused on algorithms for a recommendation for individuals. However, in many domains, it may be recommending an item, for example, movies, restaurants etc. for a group of persons for which some remarkable group recommender systems (GRSs) has been developed. GRSs satisfy a group of people optimally by considering the equal weighting of the individual preferences. We have proposed a multi-expert scheme (MES) for group recommendation using genetic algorithm (GA) MES-GRS-GA that depends on consensus techniques to further improve group recommendations. In order to deal with this problem of GRS, we also propose a consensus scheme for GRSs where consensus from multiple experts are brought together to make a single recommended list of items in which each expert represents an individual inside the group. The proposed GA based consensus scheme is modeled as many consensus schemes within two phases. In the consensus phase, we have applied GA to obtain the maximum utility offer for each expert and generated the most appropriate rating for each item in the group. In the recommendation generation phase, again GA has been employed to produce the resulting group profile, i.e. the list of ratings with the minimum sum of distances from the group members. Finally, the results of computational experiments that bear close resemblance to real-world scenarios are presented and compared to baseline GRS techniques that illustrate the superiority of the proposed model.

scholarly journals Dynamic Group Recommendation Algorithm Based on Member Activity Level

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Junjie Jia ◽  
Yewang Yao ◽  
Zhipeng Lei ◽  
Pengtao Liu
Keyword(s):  
Recommender Systems ◽  
Activity Level ◽  
Group Recommendation ◽  
Recommendation Algorithm ◽  
Group Recommender Systems ◽  
Dynamic Group ◽  
Recent Activity ◽  
Group Profile ◽  
The Impact ◽  
Group Recommender

The rapid development of social networks has led to an increased desire for group entertainment consumption, making the study of group recommender systems a hotspot. Existing group recommender systems focus too much on member preferences and ignore the impact of member activity level on recommendation results. To this end, a dynamic group recommendation algorithm based on the activity level of members is proposed. Firstly, the algorithm predicts the unknown preferences of members using a time-series-oriented rating prediction model. Secondly, considering the dynamic change of member activity level, the group profile is generated by designing a sliding time window to investigate the recent activity level of each member in the group at the recommended moment, and preference is aggregated based on the recent activity level of members. Finally, the group recommendations are generated based on the group profile. The experimental results show that the algorithm in this paper achieves a better recommendation result.

Social Presence in the Web-Based Classroom

2008 ◽  
Vol 13 (1) ◽  
pp. 46-65 ◽  
Author(s):  
Senem Yildiz
Keyword(s):  
Foreign Language ◽  
Social Interactions ◽  
Social Presence ◽  
Computer Mediated Communication ◽  
The United States ◽  
Graduate Courses ◽  
Mediated Communication ◽  
Web Based ◽  
Computer Mediated ◽  
The Social

Social presence is a theory derived from social psychology to explain social interactions in a mediated communication and is defined as the degree to which interlocutors in a communications medium perceive each other as real. This study investigates the effect of computer-mediated communication on the social presence of international students who spoke English as a foreign language in two Web-based graduate courses offered in the United States and aims to explore how linguistic and cultural differences influenced their social presence.

scholarly journals Group Recommender Systems Based on Members’ Preference for Trusted Social Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xiangshi Wang ◽  
Lei Su ◽  
Qihang Zhou ◽  
Liping Wu
Keyword(s):  
Social Networks ◽  
Recommender System ◽  
Group Recommendation ◽  
Group Activities ◽  
User Groups ◽  
Group Members ◽  
Common Interests ◽  
Data Environment ◽  
The Internet Of Things ◽  
Group Recommender

With the development of the Internet of Things (IoT), the group recommender system has also been extended to the field of IoT. The entities in the IoT are linked through social networks, which constitute massive amounts of data. In group activities such as group purchases and group tours, user groups often exhibit common interests and hobbies, and it is necessary to make recommendations for certain user groups. This idea constitutes the group recommender system. However, group members’ preferences are not fully considered in group recommendations, and how to use trusted social networks based on their preferences remains unclear. The focus of this paper is group recommendation based on an average strategy, where group members have preferential differences and use trusted social networks to correct for their preferences. Thus, the accuracy of the group recommender system in the IoT and big data environment is improved.

scholarly journals Group Recommendation for Cold Start Users using Hybrid Recommendation Technique

2019 ◽  
Vol 8 (5S3) ◽  
pp. 452-456
Keyword(s):  
Recommender System ◽  
Recommendation System ◽  
Retrieval System ◽  
Data Retrieval ◽  
Cold Start ◽  
Group Recommendation ◽  
Huge Amount ◽  
New Era ◽  
The Social ◽  
Hybrid Recommendation

Recommender system is an data retrieval system that gives customers the recommendations for the items that a customer may be willing to have. It helps in making the search easy by sorting the huge amount of data. We have progressed from the era of paucity to the new era of plethora due to which there is lot of development in the recommender system. In today’s scenario the interaction between the groups of friends, family or colleagues has increased due to the advancement in mobile devices and the social media. So, group recommendation has become a necessity in all kinds of domains. In this paper a system has been proposed using the group recommendation system based on hybrid based filtering method to overcome the cold start user issue which arises when a new user signs in and he/she doesn’t have any past records. So, the recommender system does not have enough information related to the user to recommend an item which will be of his/her interest. The dataset has been taken from the MovieLens is used in the experiment.

scholarly journals A New Approach for Fairness Increment of Consensus-driven Group Recommender Systems Based on Choquet Integral

2022 ◽  
Vol 18 (1) ◽  
pp. 0-0
Keyword(s):  
Recommender Systems ◽  
Choquet Integral ◽  
Fuzzy Measure ◽  
Group Recommendation ◽  
Consensus Process ◽  
New Approach ◽  
Group Recommender Systems ◽  
Benchmark Datasets ◽  
Group Member ◽  
Group Recommender

It has been witnessed in recent years for the rising of Group recommender systems (GRSs) in most e-commerce and tourism applications like Booking.com, Traveloka.com, Amazon, etc. One of the most concerned problems in GRSs is to guarantee the fairness between users in a group so-called the consensus-driven group recommender system. This paper proposes a new flexible alternative that embeds a fuzzy measure to aggregation operators of consensus process to improve fairness of group recommendation and deals with group member interaction. Choquet integral is used to build a fuzzy measure based on group member interactions and to seek a better fairness recommendation. The empirical results on the benchmark datasets show the incremental advances of the proposal for dealing with group member interactions and the issue of fairness in Consensus-driven GRS.

Value-driven issues throughout the development of sociological theory

2020 ◽  
pp. 147-160
Author(s):  
Gulbarshyn Chepurko ◽  
Valerii Pylypenko
Keyword(s):  
Social Interactions ◽  
Social System ◽  
Sociological Theory ◽  
Social Scientists ◽  
Social Sphere ◽  
Technological Advances ◽  
The Social ◽  
The Individual ◽  
Different Levels

The paper examines and compares how the major sociological theories treat axiological issues. Value-driven topics are analysed in view of their relevance to society in times of crisis, when both societal life and the very structure of society undergo dramatic change. Nowadays, social scientists around the world are also witnessing such a change due to the emergence of alternative schools of sociological thought (non-classical, interpretive, postmodern, etc.) and, subsequently, the necessity to revise the paradigms that have been existed in sociology so far. Since the above-mentioned approaches are often used to address value-related issues, building a solid theoretical framework for these studies takes on considerable significance. Furthermore, the paradigm revision has been prompted by technological advances changing all areas of people’s lives, especially social interactions. The global human community, integral in nature, is being formed, and production of human values now matters more than production of things; hence the “expansion” of value-focused perspectives in contemporary sociology. The authors give special attention to collectivities which are higher-order units of the social system. These units are described as well-organised action systems where each individual performs his/her specific role. Just as the role of an individual is distinct from that of the collectivity (because the individual and the collectivity are different as units), so too a distinction is drawn between the value and the norm — because they represent different levels of social relationships. Values are the main connecting element between the society’s cultural system and the social sphere while norms, for the most part, belong to the social system. Values serve primarily to maintain the pattern according to which the society is functioning at a given time; norms are essential to social integration. Apart from being the means of regulating social processes and relationships, norms embody the “principles” that can be applied beyond a particular social system. The authors underline that it is important for Ukrainian sociology to keep abreast of the latest developments in the field of axiology and make good use of those ideas because this is a prerequisite for its successful integration into the global sociological community.

The Impact of Covid 19 on Pregnant Women and Child Health

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 1367-1373
Author(s):  
Nikhil Sanjay Mujbaile ◽  
Smita Damke
Keyword(s):  
Social Issues ◽  
Middle Income ◽  
Web Based ◽  
Middle Income Countries ◽  
Low Middle Income Countries ◽  
The Social ◽  
Social Separation ◽  
The Impact ◽  
And Child Health ◽  
General Wellbeing

The Covid illness (COVID-19) pandemic has spread rapidly all through the world and has had a drawn-out impact. The Pandemic has done incredible damage to society and made genuine mental injury to numerous individuals. Mental emergencies frequently cause youngsters to deliver sentiments of relinquishment, despondency, insufficiency, and fatigue and even raise the danger of self-destruction. Youngsters with psychological instabilities are particularly powerless during the isolate and colonial removing period. Convenient and proper assurances are expected to forestall the event of mental and social issues. The rising advanced applications and wellbeing administrations, for example, telehealth, web-based media, versatile wellbeing, and far off intuitive online instruction can connect the social separation and backing mental and conduct wellbeing for youngsters. Because of the mental advancement qualities of youngsters, this investigation additionally outlines intercessions on the mental effect of the COVID-19 Pandemic. Further difficulties in Low Middle-Income Countries incorporate the failure to actualize successful general wellbeing estimates, for example, social separating, hand cleanliness, definitive distinguishing proof of contaminated individuals with self-disconnection and widespread utilization of covers The aberrant impacts of the Pandemic on youngster wellbeing are of extensive concern, including expanding neediness levels, upset tutoring, absence of admittance to the class taking care of plans, decreased admittance to wellbeing offices and breaks in inoculation and other kid wellbeing programs. Kept tutoring is critical for kids in Low Middle-Income Countries. Arrangement of safe situations is mainly testing in packed asset obliged schools. 

Social ethology of the wolverine

2018 ◽  
Author(s):  
Jeffrey P. Copeland ◽  
Arild Landa ◽  
Kimberly Heinemeyer ◽  
Keith B. Aubry ◽  
Jiska van Dijk ◽  
...  
Keyword(s):  
Social Organization ◽  
Social Interactions ◽  
Resource Availability ◽  
Social Behaviour ◽  
Social System ◽  
Group Living ◽  
Field Studies ◽  
Ecological Framework ◽  
The Social ◽  
Living Species

Social behaviour in solitary carnivores has long been an active area of investigation but for many species remains largely founded in conjecture compared to our understanding of sociality in group-living species. The social organization of the wolverine has, until now, received little attention beyond its portrayal as a typical mustelid social system. In this chapter the authors compile observations of social interactions from multiple wolverine field studies, which are integrated into an ecological framework. An ethological model for the wolverine is proposed that reveals an intricate social organization, which is driven by variable resource availability within extremely large territories and supports social behaviour that underpins offspring development.

Sign in / Sign up

Export Citation Format

Share Document