Visualizing Personalized Multifaceted ad-hoc Social Network

Amal, Saeed; Adam, Mustafa; Brusilovsky, Peter; Minkov, Einat; Segal, Zef; Kuflik, Tsvi

doi:10.1145/3386392.3397606

Cited by 1 publication

(2 citation statements)

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“…We further asked for their assessment of the multifaceted graph visualization component of the framework to determine whether it conveyed the relevant details clearly and supported information exploration. In prior work Amal et al (2020b); Amal et al (2020a); Amal et al (2020c) description of the study was described with initial results; here we provide more detailed explanations about the visualization we used and the study, detailed statistics and thorough analysis of the study and its collected feedback comments.…”

Section: Entity-relation Graph Word Cloud Visualizer and End-to-end F...mentioning

confidence: 99%

“…In addition, as the visualization of the results appeared to be highly important, being what the end user sees, this aspect was the focus of several studies. Initial results were presented in Amal et al (2019a) and improved incrementally over several iterations and demonstrated in Amal et al (2020c); Amal et al (2020b); Amal et al (2020a), all of which used the academic domain for demonstration.…”

Section: Introductionmentioning

confidence: 99%

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Person Entity Profiling Framework: Identifying, Integrating and Visualizing Online Freely Available Entity-Related Information

Amal,

Minkov,

Kuflik

2021

Preprint

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When we consider our CV, it is full of entities that we are or were associated with and that define us in some way(s). Such entities include where we studied, where we worked, who we collaborated with on a project or on a paper etc. Entities we are linked to are part of who we are and may reveal about what we are interested in. Hence, we can view any CV as a graph of interlinked entities, where nodes are entities and edges are relations between them. This study proposes a novel entity search framework that in response to a real-time query about an entity, searches, crawls, analyzes and consolidates relevant information that is freely available on the Web about the entity of interest, culminating in the generation a profile of the searched entity. Unlike typical entity search settings, in which a ranked list of entities related to the target entity over a pre-specified relation is processed, we present and visualize rich information about the entity of interest as a typed entity-relation graph without an apriori definition of the types of related entities and relations. This view is structured and compact, making it easy to understand as well as interpret. It enables the user to learn not only about the entity in question, but also about related entities, thereby obtaining a better understanding of the entity in question. We evaluated each of the framework's components separately and then performed an overall evaluation of the framework, its visualization and the interest of users in the results. The results show that the proposed framework performs entity searches, related entity identification and relation identification very well and that it satisfies users' needs.

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Section: Entity-relation Graph Word Cloud Visualizer and End-to-end F...mentioning

confidence: 99%