WHOSE – A Tool for Whole-Session Analysis in IIR

Hienert, Daniel; Hoek, Wilko van; Weber, Alina; Kern, Dagmar

doi:10.1007/978-3-319-16354-3_18

Cited by 3 publications

(3 citation statements)

References 23 publications

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“…The search process in Sowiport normally follows regular patterns which already were visualized and analyzed with the WHOSE toolkit [6] and which are comparable to the ones in other literature information systems. A first possibility is that users enter Sowiport via the homepage.…”

Section: Search Processmentioning

confidence: 86%

Where Do All These Search Terms Come From? – Two Experiments in Domain-Specific Search

Hienert

Lusky

2017

Lecture Notes in Computer Science

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Within a search session users often apply different search terms, as well as different variations and combinations of them. This way, they want to make sure that they find relevant information for different stages and aspects of their information task. Research questions which arise from this search approach are: Where do users get all the ideas, hints and suggestions for new search terms or their variations from? How many ideas come from the user? How many from outside the IR system? What is the role of the used search system? To investigate these questions we used data from two experiments: first, from a user study with eye tracking data; second, from a large-scale log analysis. We found that in both experiments a large part of the search terms has been explicitly seen or shown before on the interface of the search system.

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Section: Search Processmentioning

confidence: 86%

Where Do All These Search Terms Come From? – Two Experiments in Domain-Specific Search

Hienert

Lusky

2017

Lecture Notes in Computer Science

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“…We then measure the co-occurrence between CTS usages and positive signals on the basis of log data. For this we have used the WHOSE log analysis tool for IIR [9]. The tool allows to load log data from a digital library and to examine user session data with filters, visualizations and a detailed session list with all interactions.…”

Section: Data Set and Methodologymentioning

confidence: 99%

A Usefulness-based Approach for Measuring the Local and Global Effect of IIR Services

Hienert

Mutschke

2016

Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval

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In Interactive Information Retrieval (IIR) different services such as search term suggestion can support users in their search process. The applicability and performance of such services is either measured with different user-centered studies (like usability tests or laboratory experiments) or, in the context of IR, with their contribution to measures like precision and recall. However, each evaluation methodology has its certain disadvantages. For example, user-centered experiments are often costly and smallscaled; IR experiments rely on relevance assessments and measure only relevance of documents. In this work we operationalize the usefulness model of Cole et al. (2009) on the level of system support to measure not only the local effect of an IR service, but the impact it has on the whole search process. We therefore use a log-based evaluation approach which models user interactions within sessions with positive signals and apply it for the case of a search term suggestion service. We found that the usage of the service significantly often implicates the occurrence of positive signals during the following session steps.

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“…The mid-2000s to the mid-2010s saw a shift in focus from platform-specific [14,16,21] to web-based experimental apparatus, including interaction logging infrastructure that focused on examining the DOM. Examples of solutions from this period included MLogger [10], PooDLE [5], Search-Logger [18], Wrapper [13], UsaProxy [3,4], the framework by Hall and Toms [11], WHOSE [12], and YAS-FIIRE [20]. Some of these solutions required additional software to be installed (such as browser toolbars), while others made use of an intermediatary proxy server to inject logging code, as used in subsequent studies [2,6,7,15].…”

Section: Existing Approachesmentioning

confidence: 99%

LogUI: Contemporary Logging Infrastructure for Web-Based Experiments

Maxwell

Hauff

2021

Lecture Notes in Computer Science

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Logging user interactions is fundamental to capturing and subsequently analysing user behaviours in the context of web-based Interactive Information Retrieval (IIR). However, logging is often implemented within experimental apparatus in a piecemeal fashion, leading to incomplete or noisy data. To address these issues, we present the LogUI logging framework. We use (now ubiquitous) contemporary web technologies to provide an easy-to-use yet powerful framework that can capture virtually any user interaction on a webpage. LogUI removes many of the complexities that must be considered for effective interaction logging.

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WHOSE – A Tool for Whole-Session Analysis in IIR

Cited by 3 publications

References 23 publications

Where Do All These Search Terms Come From? – Two Experiments in Domain-Specific Search

Where Do All These Search Terms Come From? – Two Experiments in Domain-Specific Search

A Usefulness-based Approach for Measuring the Local and Global Effect of IIR Services

LogUI: Contemporary Logging Infrastructure for Web-Based Experiments

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