Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Telling How to Narrow it Down
T2 - ACM SIGIR Conference on Human Information Interaction & Retrieval
AU - Dehghani, Mostafa
AU - Jagfeld, Glorianna
AU - Azarbonyad, Hosein
AU - Olieman, Alex
AU - Kamps, Jaap
AU - Marx, Maarten
PY - 2017/3/7
Y1 - 2017/3/7
N2 - Supporting exploratory search tasks with the help of structured data is an effective way to go beyond keyword search, as it provides an overview of the data, enables users to zoom in on their intent, and provides assistance during their navigation trails. However, finding a good starting point for a search episode in the given structure can still pose a considerable challenge, as users tend to be unfamiliar with exact, complex hierarchical structure. Thus, providing lookahead clues can be of great help and allow users to make better decisions on their search trajectory.In this paper, we investigate the behaviour of users when a recommendation engine is employed along with the browsing tool in an exploratory search system. We make use of an exploratory search system that facilitates browsing by mapping the data on a hierarchical structure. We designed and developed a path recommendation engine as a feature for this system, which given a text query, ranks different browsing paths in the hierarchy based on their likelihood of covering relevant documents. We conduct a user study comparing the baseline system with the featured system.Our main findings are as follows: We observe that, using the baseline system the users tend to explore the data in a breadth-firstlike approach by visiting different data points at the same level of abstraction to choose one of them to expand and go deeper. Conversely, with browsing path recommendation (BPR) as a feature, the users tend to drive their search in a more depth-first-like approach by quickly going deep into the data hierarchy. While the users still incline to explore different parts of the search space by using BPR, they are able to restrain or augment their search focus more quickly and access smaller but more promising regions of the data. Therefore, they can complete their tasks with less time and effort.
AB - Supporting exploratory search tasks with the help of structured data is an effective way to go beyond keyword search, as it provides an overview of the data, enables users to zoom in on their intent, and provides assistance during their navigation trails. However, finding a good starting point for a search episode in the given structure can still pose a considerable challenge, as users tend to be unfamiliar with exact, complex hierarchical structure. Thus, providing lookahead clues can be of great help and allow users to make better decisions on their search trajectory.In this paper, we investigate the behaviour of users when a recommendation engine is employed along with the browsing tool in an exploratory search system. We make use of an exploratory search system that facilitates browsing by mapping the data on a hierarchical structure. We designed and developed a path recommendation engine as a feature for this system, which given a text query, ranks different browsing paths in the hierarchy based on their likelihood of covering relevant documents. We conduct a user study comparing the baseline system with the featured system.Our main findings are as follows: We observe that, using the baseline system the users tend to explore the data in a breadth-firstlike approach by visiting different data points at the same level of abstraction to choose one of them to expand and go deeper. Conversely, with browsing path recommendation (BPR) as a feature, the users tend to drive their search in a more depth-first-like approach by quickly going deep into the data hierarchy. While the users still incline to explore different parts of the search space by using BPR, they are able to restrain or augment their search focus more quickly and access smaller but more promising regions of the data. Therefore, they can complete their tasks with less time and effort.
U2 - 10.1145/3020165.3022155
DO - 10.1145/3020165.3022155
M3 - Conference contribution/Paper
SN - 9781450346771
SP - 369
EP - 372
BT - CHIIR '17 Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieva
PB - ACM
CY - New York
Y2 - 7 March 2017 through 11 March 2017
ER -