di Sciascio Maria Cecilia, Brusilovsky Peter, Trattner Christoph, Veas Eduardo Enrique
2019
A Roadmap to User-Controllable Social Exploratory Search
ACM Transactions on Interactive Intelligent System ACM
Information-seeking tasks with learning or investigative purposes are usually referred to as exploratory search. Exploratory search unfolds as a dynamic process where the user, amidst navigation, trial and error, and on-the-fly selections, gathers and organizes information (resources). A range of innovative interfaces with increased user control has been developed to support the exploratory search process. In this work, we present our attempt to increase the power of exploratory search interfaces by using ideas of social search—for instance, leveraging information left by past users of information systems. Social search technologies are highly popular today, especially for improving ranking. However, current approaches to social ranking do not allow users to decide to what extent social information should be taken into account for result ranking. This article presents an interface that integrates social search functionality into an exploratory search system in a user-controlled way that is consistent with the nature of exploratory search. The interface incorporates control features that allow the user to (i) express information needs by selecting keywords and (ii) to express preferences for incorporating social wisdom based on tag matching and user similarity. The interface promotes search transparency through color-coded stacked bars and rich tooltips. This work presents the full series of evaluations conducted to, first, assess the value of the social models in contexts independent to the user interface, in terms of objective and perceived accuracy. Then, in a study with the full-fledged system, we investigated system accuracy and subjective aspects with a structural model revealing that when users actively interacted with all of its control features, the hybrid system outperformed a baseline content-based–only tool and users were more satisfied.
di Sciascio Maria Cecilia, Brusilovsky Peter, Veas Eduardo Enrique
2018
A Study on User-Controllable Social Exploratory Search
ACM Conference on Intelligent User Interfaces IUI ACM
Information-seeking tasks with learning or investigative purposes are usually referred to as exploratory search. Exploratory search unfolds as a dynamic process where the user, amidst navigation, trial-and-error and on-the-fly selections, gathers and organizes information (resources). A range of innovative interfaces with increased user control have been developed to support exploratory search process. In this work we present our attempt to increase the power of exploratory search interfaces by using ideas of social search, i.e., leveraging information left by past users of information systems. Social search technologies are highly popular nowadays, especially for improving ranking. However, current approaches to social ranking do not allow users to decide to what extent social information should be taken into account for result ranking. This paper presents an interface that integrates social search functionality into an exploratory search system in a user-controlled way that is consistent with the nature of exploratory search. The interface incorporates control features that allow the user to (i) express information needs by selecting keywords and (ii) to express preferences for incorporating social wisdom based on tag matching and user similarity. The interface promotes search transparency through color-coded stacked bars and rich tooltips. In an online study investigating system accuracy and subjective aspects with a structural model we found that, when users actively interacted with all its control features, the hybrid system outperformed a baseline content-based-only tool and users were more satisfied.
Trattner Christoph, Parra Denis, Brusilovsky Peter, Marinho Leandro
2015
Report on the SIGIR 2015 Workshop on Social Personalization and Search
SIGIR FORUM ACM
The use of contexts –side information associated to information tasks– has been one ofthe most important dimensions for the improvement of Information Retrieval tasks, helpingto clarify the information needs of the users which usually start from a few keywords in atext box. Particularly, the social context has been leveraged in search and personalizationsince the inception of the Social Web, but even today we find new scenarios of informationfiltering, search, recommendation and personalization where the use of social signals canproduce a steep improvement. In addition, the action of searching has become a social processon the Web, making traditional assumptions of relevance obsolete and requiring newparadigms for matching the most useful resources that solve information needs. This escenariohas motivated us for organizing the Social Personalization and Search (SPS) workshop,a forum aimed at sharing and discussing research that leverage social data for improvingclassic personalization models for information access and to revisiting search from individualphenomena to a collaborative process.
Lin Yi-ling, Trattner Christoph, Brusilovsky Peter , He Daqing
2015
The impact of image descriptions on user tagging behavior: A study of the nature and functionality of crowdsourced tags
JASIST Wiley
Crowdsourcing has been emerging to harvest social wisdom from thousands of volunteers to
perform series of tasks online. However, little research has been devoted to exploring the impact
of various factors such as the content of a resource or crowdsourcing interface design to user
tagging behavior. While images’ titles and descriptions are frequently available in image digital
libraries, it is not clear whether they should be displayed to crowdworkers engaged in tagging.
This paper focuses on offering an insight to the curators of digital image libraries who face this
dilemma by examining (i) how descriptions influence the user in his/her tagging behavior and (ii)
how this relates to the (a) nature of the tags, (b) the emergent folksonomy, and (c) the findability
of the images in the tagging system. We compared two different methods for collecting image
tags from Amazon’s Mechanical Turk’s crowdworkers – with and without image descriptions.
Several properties of generated tags were examined from different perspectives: diversity,
specificity, reusability, quality, similarity, descriptiveness, etc. In addition, the study was carried
out to examine the impact of image description on supporting users’ information seeking with a
tag cloud interface. The results showed that the properties of tags are affected by the
crowdsourcing approach. Tags from the “with description” condition are more diverse and more
specific than tags from the “without description” condition, while the latter has a higher tag reuse
rate. A user study also revealed that different tag sets provided different support for search.
Tags produced “with description” shortened the path to the target results, while tags produced
without description increased user success in the search task
Trattner Christoph, Parra Denis , Brusilovsky Peter, , Marinho Leandro
2015