scispace - formally typeset
Search or ask a question

What role does ontology play in the development of recommendation systems? 


Best insight from top research papers

Ontology plays a crucial role in enhancing recommendation systems by improving accuracy, quality, and overcoming weaknesses associated with conventional recommendations. It aids in knowledge representation during the recommendation process, leading to more precise suggestions . Ontology-based recommender systems integrate domain-specific knowledge, such as user preferences, learning objects, and social network associations, to generate more effective recommendations . By incorporating ontology, recommendation systems can address issues like cold-start problems, data sparsity, and semantic interoperability, ultimately enhancing the recommendation process and user experience . The utilization of ontology methodologies and standards in building recommendation systems is crucial for their successful implementation and integration into various domains.

Answers from top 5 papers

More filters
Papers (5)Insight
Open accessJournal ArticleDOI
01 Jan 2022
50 Citations
Ontology plays a crucial role in developing recommendation systems by integrating artificial intelligence, education, and social sciences to enhance personalized learning experiences through student models and learning objects.
Ontology enhances recommendation systems by combining collaborative and content-based filtering, addressing issues like cold-start problems and data sparsity, leading to more efficient and effective recommendations.
Ontology enhances recommendation systems by improving accuracy, quality, and resolving semantic interoperability issues with heterogeneous information sources in online learning domains.
Ontology enhances recommendation systems by combining collaborative and content-based filtering, addressing issues like cold-start problems and data sparsity, leading to more efficient and effective recommendations.
Ontology enhances recommendation systems by incorporating domain knowledge, enabling precise and helpful suggestions based on relational data, improving product recommendations' accuracy and relevance.

Related Questions

Why is the ontology of a study important/?5 answersThe ontology of a study is crucial as it provides a structured framework for understanding the nature of the subject matter being studied. It helps in systematizing entities involved in the research process, forming a skeleton that guides the design procedures and operations. In drug development, understanding the ontology of toxicity mechanisms, especially hepatotoxic processes, is vital for evaluating and managing drug safety effectively. Moreover, in fields like government studies and mathematics, ontology plays a key role in defining the essence of the subject, guiding paradigm shifts, and addressing fundamental questions about the existence and nature of objects under study. Overall, ontology enhances clarity, consistency, and effectiveness in research by providing a philosophical basis for exploring the existence, nature, and relationships within a particular field of study.
What is Ontology?5 answersOntology, originating from Aristotle's philosophical inquiry, is fundamentally concerned with the nature and organization of being, posing questions about what constitutes existence and the common features shared by all entities. In the realm of computer and information science, ontology has evolved to denote a structured domain of knowledge, governed by formal rules to facilitate interpretation and utilization by computer systems. This adaptation is particularly significant in fields like bioinformatics, where ontologies enable complex queries across gene expression databases and other biological data repositories. The science of ontology extends its examination to the nature of scientific knowledge itself, distinguishing between empirical realities and the rational truths that underpin scientific inquiry, thereby delineating the boundaries of what can be rationally observed and understood. Ontology's application in technology and knowledge engineering is described as the explicit specification of conceptualization, serving as a foundational body of knowledge for various domains, including web, mining, and multi-agent systems. This philosophical discipline's relevance to computer science was first recognized by John McCarthy in 1980, marking a pivotal shift towards leveraging ontological principles for enhancing conceptual modeling and knowledge engineering within artificial intelligence and database design. The emerging domain of ontology in intelligent decision-making underscores its role in structuring unstructured data, facilitating information retrieval, and promoting data sharing and reuse across different platforms. In biomedical research, ontologies present a shared understanding of domain-specific knowledge, enhancing interoperability and the representation of real-world objects within computer systems. Despite debates over its definition, ontology's utility in knowledge engineering is undeniable, offering insights into the dynamics of conceptual change, vocabulary selection, and collaborative development. Ontological engineering has proven effective in knowledge representation, particularly within the semantic web, enabling sophisticated methodologies for developing ontologies and accessing stored knowledge. Lastly, in the field of Library and Information Science, ontology emerges as a critical tool for organizing the vast expanse of internet-based knowledge, ensuring meaningful information retrieval.
What is ontology in research?4 answersOntology in research refers to the field of Artificial Intelligence that encodes knowledge, beliefs, actions, and other mental states in a machine. It uses an ontology, which is a representation of knowledge with explicit semantics, to provide a common understanding and interoperability of data. Ontological engineering is the methodology used for developing ontologies, which are used in various fields for structuring and retrieving information from unstructured data. Different research domains, such as computational linguistics and artificial intelligence, have different definitions for ontology. Ontologies offer advancements in linguistics and terminography and can be designed using specific methodologies like VUB STAR Lab DOGMA. Ontology engineering plays a significant role and has broad application potential in various fields, including information science. The IRAO ontology focuses on modeling research artifacts in computing disciplines, including researchers, research artifact classification, relationships between artifacts, and quality evaluation benchmarks.
What is an ontology?4 answersAn ontology is a domain of knowledge structured through formal rules so that it can be interpreted and used by computers. It is a model of some aspect of the world that introduces vocabulary relevant to the domain and specifies the meaning of this vocabulary. In the context of research on ontology, philosophers try to answer questions about the nature and organization of being. In the knowledge engineering and artificial intelligence sense, an ontology is a framework for the domain knowledge of an intelligent system. It structures the knowledge and acts as a container for the knowledge, allowing multiple agents to use a common background for sharing knowledge.
What are the benefits of using ontologies for recommendation?5 answersUsing ontologies for recommendation provides several benefits. Ontologies allow for the formal representation of knowledge and relationships within a domain, enabling structured and organized data. They support reasoning and inference mechanisms, which enhance the quality of recommendations. Ontologies also facilitate reusability, allowing developers to leverage existing ontologies and vocabularies in the development process. Additionally, ontologies enable interoperability, making it easier to integrate recommendation systems with other technologies and platforms. By using ontologies, personalized recommendation systems can generate more relevant and tailored recommendations based on user preferences and profiles. Overall, ontologies enhance the quality, efficiency, and effectiveness of recommendation systems by providing a structured approach to representing and organizing data, supporting reasoning and inference, and enabling reusability and interoperability.
What is the definition of “ontology”?5 answersAn ontology is a formal description of knowledge within a specific domain, consisting of concepts and the relationships between them. It is used to facilitate communication, improve collaboration between software systems, and enhance systems engineering. Ontologies model and represent knowledge explicitly, using concepts, relations, and axioms. They offer different levels of expressiveness, from simple languages like RDF to more expressive forms like OWL. An ontology serves as a model of some aspect of the world, introducing relevant vocabulary and specifying the meaning of this vocabulary through formal languages like logic. However, there are differing opinions on the definition of ontology, with some arguing against certain proposed analyses.

See what other people are reading

What are the negative experiences of military wives during deployment?
5 answers
Military wives experience various negative experiences during deployment. Studies have shown that deployment can lead to increased levels of anxiety, depression, and stress among military spouses, impacting both male and female partners. The cancellation of deployments can also create significant stress and uncertainty for military families, affecting their overall well-being and causing disruptions in their plans and relationships. Communication challenges, conflictual communication, and lower marital satisfaction can exacerbate negative spillover effects on soldiers' work functioning during deployment, highlighting the importance of effective communication and relationship dynamics. Additionally, issues such as infidelity, trust issues, and decreased marital satisfaction have been reported among military wives during their husbands' deployment, further contributing to their negative experiences.
Does structure and crystallographic shear planes influence optical properties of molybdenum suboxides write with an introduction?
4 answers
The optical properties of molybdenum suboxides are significantly influenced by their crystal structures and the presence of crystallographic shear planes. Different tungsten suboxides exhibit varying optical behaviors based on their crystal structures. Molybdenum suboxides like Mo18O52 and Mo8O23, derived from MoO3 through crystallographic shearing, demonstrate distinct optical properties due to the involvement of lattice oxygen. Additionally, the synthesis of molybdenum oxide thin films reveals that the crystal structure impacts the band gap energy, with variations observed in the optical properties based on the inner transition states in the material. Understanding the interplay between structure, crystallographic shear planes, and oxygen vacancies is crucial for tuning the optical properties of molybdenum suboxides for applications in catalysis, optoelectronics, and other fields.
What is the Prevalence of dysmenorrhea among female students?
5 answers
The prevalence of dysmenorrhea among female students in Ethiopia is notably high. Studies conducted in different regions of Ethiopia reported varying prevalence rates. In Wolaita Soddo town high schools, the prevalence was found to be 70%. Similarly, among Haramaya University undergraduate regular students, the prevalence was reported to be 64.7%. A systematic review and meta-analysis encompassing various studies in Ethiopia estimated the pooled prevalence of dysmenorrhea among female students to be 71.69%. Factors such as age, menstrual flow duration, irregular cycles, family history of dysmenorrhea, skipping breakfast, premenstrual syndrome, early menarche, anxiety, tea consumption, and dietary habits were identified as associated factors contributing to the occurrence of dysmenorrhea among female students in Ethiopia.
What will happen if p value is greater or lesser than critical value, and?
5 answers
When the p-value is greater than the critical value, it indicates that there is not enough evidence to reject the null hypothesis. Conversely, if the p-value is less than the critical value, it suggests that there is significant evidence to reject the null hypothesis in favor of the alternative hypothesis. In the medical context, early postoperative critical values can serve as independent predictors of mortality after cardiac surgery, with higher mortality rates observed in patients with critical values. Properly controlling critical values is crucial to ensure the accuracy of statistical tests and the reliability of research findings. Additionally, the correct writing conventions for terms like "p-value" are essential to maintain consistency and clarity in statistical reporting.
What is the evolutionary history of Wolbachia as an insect endosymbiont?
5 answers
The evolutionary history of Wolbachia as an insect endosymbiont is complex, involving diverse interactions and horizontal transfers. Wolbachia infect a wide range of arthropods and nematodes, with different supergroups like A and E infecting various hosts. Studies have identified Wolbachia in diverse insect orders, with distinct patterns of infection and frequent host switching events, indicating a lack of strict cophylogeny between hosts and Wolbachia. These endosymbionts can manipulate host reproduction through mechanisms like cytoplasmic incompatibility and male killing, with strains expressing different reproductive manipulations coexisting in populations. The presence of Wolbachia in insects like mosquitoes has been harnessed for disease control programs, highlighting their significance in both evolutionary and applied contexts.
Do digital payments reduce corruption? setor?
5 answers
Digital payments have shown promise in reducing corruption in various regions. Studies in West African countries suggest that while ATM operations deter corruption, other platforms like POS, Mobile, and Online payments have increasing effects on corruption levels. Additionally, the impact of digitalization on anti-corruption efforts is evident globally, with digital reforms enhancing public integrity and transparency. Research also highlights the significant role of digitization in minimizing corruption by increasing transparency, limiting corrupt opportunities, and empowering citizens to combat corruption effectively. Furthermore, empirical analysis in European countries indicates that digitalization, particularly through internet services and digital public services, has reduced corruption prevalence in the long run, emphasizing the importance of online administrative procedures in combating corruption. Overall, digital payments and digitalization play crucial roles in combating corruption across different regions.
What is the role of alfa 1 antitripsina in the human body?
5 answers
Alfa-1 antitripsina (AAT) plays a crucial role in the human body as the most abundant protease inhibitor. It is involved in protecting tissues from enzymatic degradation, particularly in the lungs and liver. In the lungs, AAT helps maintain the structural integrity of the alveoli by inhibiting enzymes like neutrophil elastase, thus preventing tissue damage and the development of conditions like emphysema. Additionally, in the liver, mutations in the SERPINA1 gene, which encodes AAT, can lead to conditions such as chronic liver disease, cirrhosis, and hepatocellular carcinoma due to the accumulation of mutant protein in hepatocytes. Therefore, AAT deficiency can have significant implications on both pulmonary and hepatic health.
What is opportunity in fraud?
5 answers
Opportunity in fraud refers to the circumstances or conditions that enable individuals to engage in fraudulent activities. It is influenced by factors such as financial stability, external pressure, and the technical characteristics of assets. Research suggests that the perceived opportunity to commit fraud can be viewed in terms of temptation and obstacles, with cognitive factors like desire and motivation playing a role in decision-making processes related to fraud. Moreover, the presence of active governance processes and the duty of care exercised by individuals in positions of responsibility can help monitor and mitigate fraudulent deviations from real asset values, thereby reducing opportunities for fraud.
How does beef production contribute to food security and economic in primary, secondary , tertiary sectors in rural areas?
5 answers
Beef production plays a crucial role in enhancing food security and economic development across primary, secondary, and tertiary sectors in rural areas. In primary sectors, smallholder beef farming projects have been shown to improve economic status, household assets, education, technology adoption, and food security, contributing significantly to rural household development. In secondary sectors, the beef industry in developing nations like Myanmar is evolving to meet domestic and export demands, offering economic empowerment opportunities and enhancing food quality and security through education and improved production practices. Additionally, sustainable intensification of beef production systems in tropical regions, such as Brazil, has been identified as a strategy to increase meat production without compromising human food supplies, positively impacting food security and economic growth in rural areas.
Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases
5 answers
Domain adaptive code completion can be enhanced through techniques like decoupled domain databases and language models. By leveraging domain-specific adapters and a mixture-of-adapters gate, PLMs can be effectively adapted to specific coding projects, improving completion accuracy and adherence to project coding rules. Additionally, the introduction of differentiable plug-in memory in pre-training models allows for editable and scalable knowledge storage, aiding in domain adaptation, knowledge update, and in-task knowledge learning. These approaches not only enhance code completion speed but also reduce the likelihood of inducing bugs by tailoring the completion process to fit the specific requirements of each coding project.
What are some common theories that have been proposed to explain employee turnover intention?
5 answers
Various theories have been proposed to explain employee turnover intention. The Social Exchange Theory and Border Theory are commonly discussed in the literature. The Social Exchange Theory suggests that Flexible Work Arrangements (FWA) can lower turnover intention by increasing organizational commitment. On the other hand, the Border Theory posits that certain forms of FWA, such as flex time and homeworking, may increase turnover intention through heightened work-family conflicts. Additionally, the Theory of Planned Behavior, with a focus on temporal orientation, indicates that past temporal focus strengthens the relationship between turnover intention and actual turnover, while future temporal focus weakens this relationship. Moreover, the Expectancy Theory and Social Identity Theory propose that perceived corporate citizenship influences turnover intention through career development expectations and organizational identification.