A Bisociated Domain-Based Serendipitous Novelty-Recommendation Technique for Recommender Systems

Traditional recommendation paradigms such as content-based filtering (CBF) tend to recommend items that are very similar to user profile characteristics and item input, resulting in the classical twin problem of overspecialization and concentration bias of recommendations. This twin problem is prevalent with CBF recommender systems due to the utilisation of accuracy metrics to retrieve similar items, and, limiting recommendation computations to single recognized user-centered domains, rather than cross-domains.  This paper proposes a Bisociated domain-based serendipitous novelty recommendation techniques using Bisolinkers exploratory creativity discovery technique. The use of Bisolinkers enables establishing unique links between two seemingly unrelated domains, to enhance recommendation accuracy and user satisfaction. The presence of similar terms in two habitually incompatible domains demonstrates that two seemingly unrelated domains contain elements that are related and may act as a link to connect these two domains. Keywords: recommender systems, novelty, machine learning, outlier detection, bisociation &nbsp

Fake Profile Identification on Online Social Networks

Online social networks are web-based applications that allow user to communicate and share knowledge and information. The number of users who make use of these platforms are experiencing rapid growth both in profile creation and social interaction. However, intruders and malicious attackers have found their way into the networks, using fake profiles, thus exposing user to serious security and privacy problem.  Every user in the online social network should verify and authenticate their identities, with the other users as they interact. However, currently verification of user’s profiles and identities is faced with challenges, to the extent that a user may represent their identity with many profiles without any effective method of identity verification. As a result of this vulnerability, attackers create fake profiles which they use in attacking the online social system. In addition, online social networks use a logically centered architecture, where their control and management are under a service; provider, who must be entrusted with the security of data and communication traces; this further increases the vulnerability to attacks and online threats. In this paper, we demonstrate the causes and effects of fake profiles on online social networks, and then provide a review of the state-of-the-art mechanism for identifying and mitigating fake profiles on online social networks. Keywords: online social networks, fake profiles, sybil attack, fake account

Adoption of Artificial Intelligence in Agriculture in the Developing Nations: A Review

While most developing nations rely largely on rain-fed agriculture and use of traditional mechanisms to mitigate and control emergency crop pests and disease invasion and their effects, global warming has severely affected the agricultural productivity in these regions making them vulnerable to food insecurity. Inadequate extension services and hardly accessible information from agricultural agencies both at the local and national governments has made arable lands in these countries unproductive. In an attempt to address this problem, this paper argues that leveraging digital tools could support the farmers to improve the productivity of their farms amidst the aforementioned challenges. Emerging technologies such as artificial intelligence (AI) and machine learning (ML) enable development of applications that could provide the farmers with timely, accurate and relevant agricultural information needed to support decision-making processes. Thus, this paper sought to establish the role of AI in agriculture in mitigating the challenges faced by farmers in developing nations. Keywords: Artificial Intelligence (AI), e-agriculture, Information Communication and Technology (ICT), Internet of Things (IoT), Smart Farming, Support Vector Machines (SVM), Unmanned Aerial Vehicles (UAV