This position paper supports the idea of the information dialog between IR systems and users during an information search task. In order to satisfy the communication and interaction needs of humans, IR systems should explicitly support the cognitive abilities of the users. An information dialogue which does not only support an individual query but also the complete search process is necessary. Only in this way it is possible to satisfy an information need.
Information seeking is usually not a single step to recover a piece of information, but a cyclic, highly interactive process with the aim to satisfy a speci c information need. Within such a process the user builds a cognitive model, which helps her to re ect and advance the search process.Within user interfaces, it is necessary to integrate tools and functionalities within existing tools, in order to develop this cognitive perception and derive a context model of the users. Requirements for this are logging of all user and system activities ranging from entered queries to the result sets, tools to visualize the context and system support based on a context analysis.
In order to support the statement of the introduction, we would like to dwell on three aspects.
As stated above we need to log all user and system activities and the corresponding result sets within a task to catch the users context. From the experience one knows that a search task is usually not concluded with the rst query. Rather a working context through the interaction is elaborated. When this understanding becomes clear, there must be some kind of accompanying information dialogue. A dialogue consists of a sequence of activities and results.
In the past initial research ([
The process of the related research was consistent: Starting from the support and improvement of individual queries, up to a more global view of the search process and dialogue. But this global view must become granular again. In order to interpret a process or a dialog, the individual steps must be identi ed and formalized within this dialog.
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1. Exploration: The access to set of information objects in the form of a query and the visualization and realisation of the produced result set de nes the Exploration. A change respectively an enlargement of the informal context is caused by it. 2. Focus: The focus set represents the subset of information objects of a result set which reach the eld of vision of the user through a visualisation and is the result of the activity Focus 3. Navigation: The movement within a set of information objects (information room) or between di erent information rooms. This causes a change of the focus. 4. Inspection: Inspection is used for the cognitive determination of the state of an information object. 5. Evaluation: Evaluation gives the system a feedback of the user's understanding of relevance and appoints the veri ed recall set. 6. Store: This activity allows to store found documents.
It either happens logically in form of a storage box on the user interface or physically when a document is downloaded or printed.
Based on these de nitions we can log a dialog or the whole search process with the system. Because some of these acitivities correlate we can identify three interactive modes. The user nds oneself in one of theses modes and will change cicular the mode. The rst mode is every time access. Within this mode there is only one activity, Exploration. Already after the rst Exploration the user changes into the second mode Orientation. Activities for this mode are Navigation, Focus and Inspection. The user is now in the ability to change the visual as well as the informational focal point in an information visualisation of the dialogue context. The mode Assessment is reached, if the user nds objects of interest during his ispection. For this mode the activities Evaluation and Store are available. They help to express the users appreciation of relevance and to de ne the identi ed recall set.
Beside di erent models for information searching ([
Interactive Session 1
The past research ([
This statement leads us to the second aspect of our
position. If we understand search as a process, whose
progression lls our context, then we need also support, in order to
understand and interpret this context. So the visualization
of results must go beyond the usual measure. Especially the
di erent sets of information objects shown in [
A rst prototype is developed which visualize the di erent sets of information objects during an information search
R rtotal: Context set ke,1,ke,2,ke,3: Explored recall set kf,1,kf,2,kf,3: Fokused recall set kv,1,kv,2,kv,3: Verified recall set process (see gure 3). In a next step we will evaluate this prototype.
Following the formal description of the information dialogue and given the demands we want to introduce the Da odil-system as an experimental system for further development and evaluation of the above described model. It provides already, up to a certain extend, the demand for mapping the user activities to existing available tools.
With the information of our context model including the search path we identifed the following challenges: Relevance Feedback The users implicit and explicit relevance assessments must be captured and related to possible relevant documents.
Search strategy With the help of the user or by monitoring the activities the system must provide di erent search strategies to raise e ciency.
Collaborative recommendations By logging many different searches in form of a set of activities, it is possible to support a user through collaborative recommendations. Analyzing a new search from the beginning, the system is able to identify similar stored search processes. If this knowledge is visualized for the user, he could get bene t for his own search task.
The idea of this position paper is to support users within a search task by logging all activities between the user and the system. For this, we are able to visualize the context and make it cognitive perceptible. Furthemore, we are able to draw conclusions from this activities. This captured information represents the basis to further understand and support the user. Such support could be done through recommendation via implicit relevance feedback as well as collaborative recommendations through other users in a similar situation. We think, that given the context model within the Da odil-Framework, we are able to understand and categories user behavior and provide solid data to support system oriented IR evaluation, e.g. based on user simulation.
We currently investigate and evaluate our research using
the Da odil - framework ([
Task manager: A tool to capture and log all activities and resulting sets of information objects of a search task over more then one session.
Visualization: Visualize the context and search path with help of venn diagrams.
Relevance feedback: Interpretation of activities as implicit relevance feedback with term suggestions and reranked result lists.