What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- World Wide Web
Tsvi Kuflik mostly deals with Recommender system, World Wide Web, Collaborative filtering, Data mining and Personalization.
The study incorporates disciplines such as Variety, Context and Personal experience in addition to World Wide Web.
Tsvi Kuflik works mostly in the field of Collaborative filtering, limiting it down to topics relating to Domain and, in certain cases, Mediation and Information retrieval, as a part of the same area of interest.
His Data mining research is multidisciplinary, incorporating elements of Empirical research, Requirements analysis, Process and Access control.
His Personalization study incorporates themes from User modeling, The Internet and Social web.
His studies in User modeling integrate themes in fields like Adaptation, Human–computer interaction, User interface design, Interactivity and Component.
His most cited work include:
- Second workshop on information heterogeneity and fusion in recommender systems (HetRec2011) (215 citations)
- Mediation of User Models: for Enhanced Personalization in Recommender Systems (168 citations)
- Adaptive, intelligent presentation of information for the museum visitor in PEACH (155 citations)
What are the main themes of his work throughout his whole career to date?
Tsvi Kuflik mainly focuses on World Wide Web, Human–computer interaction, Personalization, Multimedia and User modeling.
In the field of World Wide Web, his study on Recommender system and Mobile device overlaps with subjects such as Visitor pattern.
Tsvi Kuflik is studying Collaborative filtering, which is a component of Recommender system.
His Human–computer interaction study integrates concerns from other disciplines, such as Smart environment and Component.
His Personalization research includes themes of Information visualization and Point.
His study in User modeling is interdisciplinary in nature, drawing from both Mediation, Adaptation, User requirements document and User interface design, User experience design.
He most often published in these fields:
- World Wide Web (33.80%)
- Human–computer interaction (22.54%)
- Personalization (20.19%)
What were the highlights of his more recent work (between 2015-2021)?
- World Wide Web (33.80%)
- Personalization (20.19%)
- Human–computer interaction (22.54%)
In recent papers he was focusing on the following fields of study:
Tsvi Kuflik mainly investigates World Wide Web, Personalization, Human–computer interaction, Multimedia and Recommender system.
His World Wide Web research integrates issues from Domain, Visualization, Point and User studies.
His Personalization research is multidisciplinary, incorporating perspectives in Intelligent decision support system, Information visualization, User modeling and Position paper.
The Human–computer interaction study combines topics in areas such as Creative visualization, Context, Popularity and Exploratory research.
In his study, Smart environment is strongly linked to Eye tracking, which falls under the umbrella field of Multimedia.
Tsvi Kuflik interconnects Recall, Focus and Artificial intelligence in the investigation of issues within Recommender system.
Between 2015 and 2021, his most popular works were:
- Automating a framework to extract and analyse transport related social media content: The potential and the challenges (40 citations)
- Visualizing museum visitors' behavior: Where do they go and what do they do there? (30 citations)
- Incorporating Dwell Time in Session-Based Recommendations with Recurrent Neural Networks. (29 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- World Wide Web
Tsvi Kuflik spends much of his time researching World Wide Web, Recommender system, Human–computer interaction, Context and Multimedia.
His studies deal with areas such as Information retrieval and User studies as well as World Wide Web.
The various areas that Tsvi Kuflik examines in his Recommender system study include Recurrent neural network, Session, Data science and Artificial intelligence.
His work on Augmented reality as part of general Human–computer interaction research is often related to Visitor pattern and Natural, thus linking different fields of science.
His Context research integrates issues from Semantic Web, Digitization and Personalization.
His Personalization research incorporates themes from Content creation, Visualization, Information visualization and Relation.
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