In interactive information retrieval, researchers consider the user behaviour towards systems and search tasks in order to adapt search results and to improve the search experience of users. Analysing the… Click to show full abstract
In interactive information retrieval, researchers consider the user behaviour towards systems and search tasks in order to adapt search results and to improve the search experience of users. Analysing the users’ past interactions with the system is one typical approach. In this paper, we analyse the user behaviour in retrieval sessions towards Marcia Bates’ search stratagems such as “Footnote Chasing”, “Citation Searching”, “Keyword Searching”, “Author Searching” and “Journal Run” in a real-life academic search engine. In fact, search stratagems represent high-level search behaviour as the users go beyond simple execution of queries and investigate more of the system functionalities. We performed analyses of these five search stratagems using two datasets extracted from the social sciences search engine sowiport. A specific focus was the detection of the search phase and frequency of the usage of these stratagems. In addition, we explored the impact of these stratagems on the whole search process performance. We addressed mainly the usage patterns’ observation of the stratagems, their impact on the conduct of retrieval sessions and explored whether they are used similarly in both datasets. From the observation and metrics proposed, we can conclude that the utilisation of search stratagems in real retrieval sessions leads to an improvement of the precision in terms of positive interactions. For both datasets (SUSS 14–15 and SUSS 16–17), the user behaviour was similar as all stratagems appear most frequently in the middle of a session. However, the difference is that “Footnote Chasing”, “Citation Searching” and “Journal Run” appear mostly at the end of a session while Keyword and Author Searching appear typically at the beginning. Thus, we can conclude from the log analysis that the improvement of search functionalities including personalisation and/or recommendation could be achieved by considering references, citations, and journals in the ranking process.
               
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