Everybody,
            <i>More or Less</i>
            , likes Serendipity

Maccatrozzo, Valentina; Everdingen, Eveline van; Aroyo, Lora; Schreiber, Guus

doi:10.1145/3099023.3099064

Cited by 8 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The article indicates that the recommender system is critical to this new social experience. In an article by Maccatrozzo, van Everdingen, Aroyo, and Schreiber (2017), the authors establish that everybody has a varying taste for serendipity. The authors argue that serendipity is critical for advancing recommender system applications in various fields.…”

Section: Serendipity and Technologymentioning

confidence: 99%

Review of User Interface-Facilitated Serendipity in Recommender Systems

Afridi

Olsson

2023

International Journal of Interactive Communication Systems and Technologies

View full text Add to dashboard Cite

Serendipity has become a desirable quality in designing recommender systems and user interfaces, hence offering a new measurement for system quality. At the same time, recognizing serendipitous experiences and determining their value is difficult due to their subjective nature. This review builds on 10 studies of user interfaces facilitating serendipity studies and attempts to understand the patterns that guide relevant user interface designs in recent recommender systems. This study furthers our understanding of turning the elusive experience of serendipity into more actionable user interface designs and patterns. The key findings are as follows. First, user controls and visualizations have facilitated serendipity, but studies of recommender systems have not gained considerable attention. Second, frameworks instrumental for user-interface-facilitated serendipity have not gained the researcher's worthy attention. Third, developing countries need to explore serendipity-facilitating recommender systems with more diverse users and more prominent test cases.

show abstract

Section: Serendipity and Technologymentioning

confidence: 99%

Review of User Interface-Facilitated Serendipity in Recommender Systems

Afridi

Olsson

2023

International Journal of Interactive Communication Systems and Technologies

View full text Add to dashboard Cite

show abstract

“…Iaquinta et al (2008) found that the concept of serendipity in recommendations is highly subjective, and that serendipity as a quality of recommended information is difficult to assess. Many developers (Herlocker, Konstan, Terveen, & Riedl, 2004;Maccatrozzo et al, 2017;Niu & Abbas, 2017) have defined serendipity in returned results as those items which hold both surprise and value for the end user. Ge et al (2010) identified key features of serendipitous results as items which have not been previously discovered or expected by the user and are considered to be interesting, relevant and useful to the user.…”

Section: Serendipity and Information Recommender Systemsmentioning

confidence: 99%

“…While most algorithms focus on the accuracy of the retrieved results, there has been increased interest in the development of algorithms that will go beyond accuracy to support novelty, diversity and serendipity with the retrieved results. Development of recommender systems that focus on providing ‘serendipitous’ encounters have been the focus of several information behavior studies (Erdelez, ; Makri, Toms, McCay‐Peet, & Blandford, ; McCay‐Peet & Toms, ; Wopereis & Braam, ) and human computer interaction studies (Dahroug et al, ; Fazeli et al, ; Maccatrozzo et al, ; Niu & Abbas, ) in recent years. One challenge to the development of recommender systems that support serendipity is identifying the type of information that end users will find surprising but also useful.…”

Section: Introductionmentioning

confidence: 99%

“…From the development of Post-it® notes (Schwager, 2000) and Super-glue® (Raja, 2016) to the discovery of x-rays (Shapiro, 1986) and the development of Viagra (Lesko, 2017), society has benefitted from these 'pleasant surprises'. The process of serendipity connects seemingly unrelated concepts in what can appear to be a highly subjective manner and relies on unique characteristics of the encountering individual to make these fortunate connections (Iaquinta et al, 2008;Maccatrozzo, van Everdingen, Aroyo, & Schreiber, 2017). When viewed from an information behavior perspective, however, it becomes evident that serendipity involves behaviors that are much more purposeful than mere accidents.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distraction to illumination: Mining biomedical publications for serendipity in research

Allen

Erdelez

2018

Proc. Assoc. Info. Sci. Tech.

View full text Add to dashboard Cite

As our technological capabilities for filling information needs improve, developers seek to more effective ways to support different aspects of the users' experience. One aspect that is gaining attention as an emerging support area is serendipity. However, supporting serendipity within a recommender system is difficult because the experience is unexpected and, therefore unpredictable. While researchers agree that algorithms to support serendipity need to be able to provide a balance of surprise and value to the end user (Niu & Abbas, 2017), an understanding of how to provide that balance has not yet been realized. Information that could be puzzling or distracting to someone as they go about their research activities may provide the trigger someone else needs to make a serendipitous connection in their research. Reports of serendipitous occurrences in research settings have been identified in research commentaries (Campanario, 1996) and within full‐text research articles (Allen, Erdelez, & Marinov, 2013). This paper investigates the feasibility of automating the identification of information encounters in full‐text research articles. This study contributes to the development of algorithms for supporting serendipity in information systems. We identified four variables that are useful for predicting information encounters in 25‐35% of the instances. While we should continue to search for additional predictive variables, these findings present a novel approach to undertaking the support of serendipity in information systems.

show abstract

“…We introduced the usage of LOD paths in content-based recommender system in a previous work [20]. An LOD path is an ordered set of types and properties, which connects two types, T 1 and T l+1 :…”

Section: Novelty Checkmentioning

confidence: 99%

Sirup

Maccatrozzo

Terstall

Aroyo

et al. 2017

Proceedings of the 22nd International Conference on Intelligent User Interfaces

View full text Add to dashboard Cite

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

show abstract

Everybody, More or Less , likes Serendipity

Cited by 8 publications

References 3 publications

Review of User Interface-Facilitated Serendipity in Recommender Systems

Review of User Interface-Facilitated Serendipity in Recommender Systems

Distraction to illumination: Mining biomedical publications for serendipity in research

Sirup

Contact Info

Product

Resources

About