Personalized Search

Ahn, Jae‐wook; Brusilovsky, Peter; Han, Shuguang

doi:10.1145/2678025.2701410

Cited by 13 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We fit the structural model with a mean-and varianceadjusted weighted least squares estimator, which again yielded an admissible model fit, χ 2 (58) = 79.13, p = .03 (χ 2 Figure 6 is the cornerstone to validate our hypotheses regarding user experience. Regression pathways report standardized coefficients (β) and robust standard errors.…”

Section: Resultsmentioning

confidence: 99%

“…Another line of research applies visualizations and interactions to enrich the user interface, thereby relying on the user to actively steer the search process. These search UIs often provide some sort of relevance-to-query explanations to augment ordered lists [29,31,56,59,66] or using spatial layouts that exploit reference points, such as query terms, keywords or concepts and convey relevance by arranging documents around them [1,2,48]. More recent approaches towards fluid information exploration seek to provide hypercues linking entities in the information space [36], employing techniques such as interactive intent modeling of user profiles [33,60,61], visual re-ranking in spatial relevance maps [37].…”

Section: Exploratory Searchmentioning

confidence: 99%

See 1 more Smart Citation

Understanding the effects of control and transparency in searching as learning

Sciascio

Veas

Barria-Pineda

et al. 2020

Proceedings of the 25th International Conference on Intelligent User Interfaces

View full text Add to dashboard Cite

In this paper, we analyze the benefits of adopting user interfaces that offer control and transparency for searching in contexts of learning activities. Concretely, we conducted a user study with pharmacy students performing a problem-solving task in the course of a university lecture. The task involved finding scientific papers containing relevant information to solve a clinical case. Students were split into two independent groups and assigned one search tool to perform the task. The baseline group worked with PubMed, a popular search engine in the life sciences domain, whereas the second half of the class was assigned an exploratory search system (ESS) designed for control and transparency. In the analysis, we cover the objective and subjective dimensions of the task outcomes. Firstly, the objective analysis addresses the inherent difficulty of the search task in a learning scenario and identifies certain improvements in performance for those students using the ESS, most notably when searching for primary-source content. The subjective analysis investigates the human factors side, providing evidence that the ESS effectively increases the perception of control and transparency and is able to produce a better user experience. Lastly, we report on perceived learning as a subjective dimension measured separately from user experience. CCS CONCEPTS • Information systems → Web searching and information discovery; Search interfaces; • Applied computing → Interactive learning environments.

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Exploratory Searchmentioning

confidence: 99%

Understanding the effects of control and transparency in searching as learning

Sciascio

Veas

Barria-Pineda

et al. 2020

Proceedings of the 25th International Conference on Intelligent User Interfaces

View full text Add to dashboard Cite

show abstract

“…Interactive interfaces that enable transparent control on user models have recently become popular [8,66,95,96]. The idea behind these approaches is that, as opposite to visualizing results, the user model is visualized and the user can interactively provide feedback on the search intentions using the visualization.…”

Section: Visual Interfaces In Searchmentioning

confidence: 99%

Interactive Intent Modeling for Exploratory Search

Ruotsalo

Peltonen

Eugster

et al. 2018

ACM Trans. Inf. Syst.

View full text Add to dashboard Cite

Exploratory search requires the system to assist the user in comprehending the information space and expressing evolving search intents for iterative exploration and retrieval of information. We introduce interactive intent modeling, a technique that models a user's evolving search intents and visualizes them as keywords for interaction. The user can provide feedback on the keywords, from which the system learns and visualizes an improved intent estimate and retrieves information. We report experiments comparing variants of a system implementing interactive intent modeling to a control system. Data comprising search logs, interaction logs, essay answers, and questionnaires indicate significant improvements in task performance, information retrieval performance over the session, information comprehension performance, and user experience. The improvements in retrieval effectiveness can be attributed to the intent modeling and the effect on users' task performance, breadth of information comprehension, and user experience are shown to be dependent on a richer visualization. Our results demonstrate the utility of combining interactive modeling of search intentions with interactive visualization of the models that can benefit both directing the exploratory search process and making sense of the information space. Our findings can help design personalized systems that support exploratory information seeking and discovery of novel information.

show abstract

“…The same approach can be used to generate adaptive learning content based on the some content elements. So the creation of SLC implies personalized search of learning resources [2] and adaptive visualization of information retrieval [1].…”

Section: Introductionmentioning

confidence: 99%

Ontology-Based Learning Content Management System in Programming Languages Domain

Kultsova

Anikin

Zhukova

et al. 2015

Communications in Computer and Information Science

View full text Add to dashboard Cite

Abstract. This paper presents an ontology-based learning content management system to create the personal collections of learning resources. To manage the learning process the set of ontologies (ontologies of learning course domain, electronic learning resources, learner's profile and personal collections) is elaborated as well as the two-stage method and algorithms for retrieval and integration of distributed learning resources into personal collections. In the framework of considered ontology-based approach the software architecture and web application for creating the personal collections of learning resources have been developed. Developed system was applied for creation of personal collections for the course "Programming Languages. C++" in Volgograd State Technical University.

show abstract

Personalized Search

Cited by 13 publications

References 24 publications

Understanding the effects of control and transparency in searching as learning

Understanding the effects of control and transparency in searching as learning

Interactive Intent Modeling for Exploratory Search

Ontology-Based Learning Content Management System in Programming Languages Domain

Contact Info

Product

Resources

About