Web search engines have become the dominant tools for finding information on the Internet. Due to their popularity, users apply them to a wide range of search needs, from simple look-ups to rather complex information tasks. This paper presents the results of a study that investigated the characteristics of these complex information needs in the context of Web search engines. The aim of the study was to find out more about (1) what makes complex search tasks distinct from simple tasks and whether it is possible to find simple measures for describing their complexity, (2) whether search success for a task can be predicted by means of unique measures, and (3) whether successful searchers show a different behaviour than unsuccessful searchers. The study includes 56 ordinary Web users who carried out a set of 12 search tasks using current commercial search engines. Their behaviour was logged with the Search-Logger tool. The results confirm that complex tasks show significantly different characteristics than simple tasks. Successful search behaviour can be distinguished from unsuccessful search behaviour. The implications of these findings for search engine vendors are discussed.

Search engines are the preferred tools for finding information on the Web. They are advancing to be the common helpers to answer any of our search needs. We use them to carry out simple look-up tasks and also to work on rather time consuming and more complex search tasks. Yet, we do not know very much about the user performance while carrying out those tasks -especially not for ordinary users. The aim of this study was to get more insight into whether Web users manage to assess difficulty, time effort, query effort, and task outcome of search tasks, and if their judging performance relates to task complexity. Our study was conducted with a systematically selected sample of 56 people with a wide demographic background. They carried out a set of 12 search tasks with commercial Web search engines in a laboratory environment. The results confirm that it is hard for normal Web users to judge the difficulty and effort to carry out complex search tasks. The judgments are more reliable for simple tasks than for complex ones. Task complexity is an indicator for judging performance.

Search engines such as Google, Bing, and Yahoo, supplemented by other information search portals like Wikipedia, have become the means for searching information on the Internet. Along with the increasing popularity of search engines, the academic interest in search has shifted from analysing simple look-up query and response patterns to analysing rather complex information seeking needs. Current search tools seem to support complex search not as well as they do in the case of look-up. Especially support for aggregating search results from multiple search-queries, taking into account discoveries made during a complex search task, and synthesizing them to some newly compiled document of information is only at the beginning and motivates researchers to develop new tools for supporting those information seeking techniques. We focus in this work on the exploratory search concepts aggregation, discovery, and synthesis. Our idea is that these are today the most time consuming activities, especially when fulfilling a complex information need. We will use these three concepts throughout this paper to evaluate different approaches in exploratory search and give an overview of the state of the art and current ongoing research in respect to these concepts.

In this paper, we focus on a specific class of search cases: exploratory search tasks. To describe and quantify their complexity, we present a new methodology and corresponding tools to evaluate the user behavior when carrying out exploratory search tasks. These tools consist of a client called Search-Logger, and a server side database with frontend and an analysis environment. The client is a plug-in for Firefox web browsers. The assembly of the Search-Logger tools can be used to carry out user studies for search tasks independent of a laboratory environment. It collects implicit user information by logging a number of significant user events. Explicit information is gathered via user feedback in the form of questionnaires before and after each search task. We also present the results of a pilot user study. Some of our main observations are: When carrying out exploratory search tasks, classic search engines are mainly used as an entrance point to the web. Subsequently users work with several search systems in parallel, they have multiple browser tabs open and frequently use the clipboard to memorize, analyze and synthesize potentially useful data and information. Exploratory search tasks typically consist of various sessions and can span from hours up to weeks.

New developments and decreasing costs of electronic appliances enable the realization of pervasive systems in our daily environment. In our work, we focus on eHome systems. The price of individual development and adaption of the software making up these systems is one of the major problems preventing their large-scale adoption. In this paper, we introduce an approach built upon functionality composition for automatic service configuration in different environments. We transform the repetitive development process to a single development process followed by a repetitive configuration process. This configuration process is supported by our tool suite, the eHomeConfigurator. The result is a configuration graph, capable of describing dependencies and contexts of components in the eHome field. The tool suite is used to configure and deploy various services on different home environments. Compared to the classical development process, the effort for setting up eHome systems is reduced significantly.