We present a web-based diary study on location-based search behavior using a mobile search engine. To capture users' location-based search behavior in a ubiquitous setting, we use a web-based diary tool that collects users' detailed mobile search activity, their location and diary entries. This method enables us to capture users' explicit behavior (query made), their implicit intention (motivation behind search) and the context (spatial, temporal, and social) in which the search was carried out. The results of the study show that people tend to stick closely to regularly used routes and regularly visited places, e.g. home and work. We also found that most location-based searches are conducted while in the presence of others. We summarize our findings and offer suggestions to improve location-based search by using features such as location-based service mash-ups.

Embodied social agents are programmed to display human‐like social behaviour to increase intuitiveness of interacting with these agents. It is yet unclear what the differences in peoples' responses are to different types of agents' social behaviours. One example is touch. Despite robots' physical embodiment and increasing autonomy, the effect of communicative touch has been a mostly overlooked aspect of human‐robot interaction. This video‐based, 2 × 2 between‐subject survey experiment (N = 119) found that the combination of touch and proactivity influenced whether people saw the robot as machine‐like and dependable. Furthermore, participants' attitude toward robots in general was found to influence perceived closeness between a human and a robot. Results show that communicative touch could be considered a more appropriate behaviour for proactive agents rather than reactive agents. Also, people that are generally more positive towards robots find robots that interact by touch less machine‐like. These effects illustrate that careful consideration is necessary when incorporating social behaviours in agents' physical interaction design. Copyright © 2009 John Wiley & Sons, Ltd.

a b s t r a c tIn this article we describe a Semantic Web application for semantic annotation and search in large virtual collections of cultural-heritage objects, indexed with multiple vocabularies. During the annotation phase we harvest, enrich and align collection metadata and vocabularies. The semantic-search facilities support keyword-based queries of the graph (currently 20 M triples), resulting in semantically grouped result clusters, all representing potential semantic matches of the original query. We show two sample search scenario's. The annotation and search software is open source and is already being used by third parties. All software is based on established Web standards, in particular HTML/XML, CSS, RDF/OWL, SPARQL and JavaScript.

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We report on our user study on the information seeking behavior of cultural heritage experts and the sources they use to carry out search tasks. Seventeen experts from nine cultural heritage institutes in the Netherlands were interviewed and asked to answer questionnaires about their daily search activities. The interviews helped us to better understand their search motivations, types, sources and tools. A key finding of our study is that the majority of search tasks involve relatively complex information gathering. This is in contrast to the relatively simple fact-finding oriented support provided by current tools. We describe a number of strategies that experts have developed to overcome the inadequacies of their tools. Finally, based on the analysis, we derive general trends of cultural heritage experts' information seeking needs and discuss our preliminary experiences with potential solutions.