Fitted Q-iteration and functional networks for ubiquitous recommender systems
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DOI: 10.1007/s00500-016-2248-1
Abstract: Ubiquitous recommender systems facilitate users on-location by personalized recommendations of items in the proximity via mobile devices. Due to a high variability of situations and preferences, an efficient resource processing is needed in order to… read more here.
Keywords: functional networks; recommender; ubiquitous recommender; fitted iteration ... See more keywords
An explanation-based approach for experiment reproducibility in recommender systems
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DOI: 10.1007/s00521-019-04274-x
Abstract: The offline evaluation of recommender systems is typically based on accuracy metrics such as the Mean Absolute Error and the Root Mean Squared Error for error rating prediction and Precision and Recall for measuring the… read more here.
Keywords: explanation based; recommender systems; based approach; approach ... See more keywords
Revisiting recommender systems: an investigative survey
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DOI: 10.1007/s00521-024-10828-5
Abstract: This paper provides a thorough review of recommendation methods from academic literature, offering a taxonomy that classifies recommender systems (RSs) into categories like collaborative filtering, content-based systems, and hybrid systems. It examines the effectiveness and… read more here.
Keywords: recommender; investigative survey; recommender systems; systems investigative ... See more keywords
Recommender systems in model-driven engineering
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DOI: 10.1007/s10270-021-00905-x
Abstract: Recommender systems are information filtering systems used in many online applications like music and video broadcasting and e-commerce platforms. They are also increasingly being applied to facilitate software engineering activities. Following this trend, we are… read more here.
Keywords: recommender; systems model; model driven; recommender systems ... See more keywords
Proposing improved meta-heuristic algorithms for clustering and separating users in the recommender systems
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DOI: 10.1007/s10660-021-09478-9
Abstract: To offer an appropriate recommendation to customers in recommender systems, the issue of clustering and separating users with different tastes from the rest of people is of significant importance. The MkMeans + + algorithm is a technique for… read more here.
Keywords: recommender systems; separating users; clustering separating; mkmeans algorithm ... See more keywords
Understanding customer loyalty-aware recommender systems in E-commerce: an analytical perspective
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DOI: 10.1007/s10660-025-09954-6
Abstract: The selection of relevant variables is critical for providing personalized product and service recommendations on e-commerce businesses. However, the integration of e-loyalty-related features into recommender systems remains underexplored. This study aims to investigate the impact… read more here.
Keywords: customer loyalty; recommender systems; commerce businesses; loyalty ... See more keywords
User Personality and User Satisfaction with Recommender Systems
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DOI: 10.1007/s10796-017-9782-y
Abstract: In this study, we show that individual users’ preferences for the level of diversity, popularity, and serendipity in recommendation lists cannot be inferred from their ratings alone. We demonstrate that we can extract strong signals… read more here.
Keywords: diversity popularity; recommender systems; personality; popularity serendipity ... See more keywords
An overview of recommender systems in the internet of things
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DOI: 10.1007/s10844-018-0530-7
Abstract: The Internet Of Things (IoT) is an emerging paradigm that envisions a networked infrastructure enabling different types of devices to be interconnected. It creates different kinds of artifacts (e.g., services and applications) in various application… read more here.
Keywords: systems internet; recommendation; overview recommender; internet things ... See more keywords
Inferring preferences in ontology-based recommender systems using WOWA
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DOI: 10.1007/s10844-018-0532-5
Abstract: In content-based semantic recommender systems the items to be considered are defined in terms of a set of semantic attributes, which may take as values the concepts of a domain ontology. The aim of these… read more here.
Keywords: inferring preferences; information; ontology; preferences ontology ... See more keywords
A survey on group recommender systems
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DOI: 10.1007/s10844-018-0542-3
Abstract: Recommender systems are increasingly used in various domains like movies, travel, music, etc. The rise in social activities has increased the usage of recommender systems in general and group recommender systems in particular. A group… read more here.
Keywords: systems survey; group recommender; recommender systems; group ... See more keywords
Towards psychology-aware preference construction in recommender systems: Overview and research issues
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DOI: 10.1007/s10844-021-00674-5
Abstract: User preferences are a crucial input needed by recommender systems to determine relevant items. In single-shot recommendation scenarios such as content-based filtering and collaborative filtering, user preferences are represented, for example, as keywords, categories, and… read more here.
Keywords: preference construction; recommendation; recommender systems; psychology ... See more keywords