Using contextual queries

Search engines generally treat search requests in isolation. The results for a given query are identical, independent of the user, or the context in which the user made the request. An approach is demonstrated that explores implicit contexts as obtained from a document the user is reading. The approach inserts into an original (web) document functionality to directly activate context driven queries that yield related articles obtained from various information sources

Mining microarray datasets aided by knowledge stored in literature

DNA microarray technology produces large amounts of data. For data mining of these datasets, background information on genes can be helpful. Unfortunately most information is stored in free text. Here, we present an approach to use this information for DNA microarray data mining

Improving groupware design for loosely coupled groups

Loosely coupled workgroups are common in the real world, and workers in these groups are autonomous and weakly interdependent. They have patterns of work and collaboration that distinguish them from other types of groups, and groupware systems that are designed to support loose coupling must address these differences. However, they have not been studied in detail in Computer-Supported Cooperative Work (CSCW), and the design process for these groups is currently underspecified. This forces designers to start from scratch each time they develop a system for loosely coupled groups, and they must approach new work settings with little information about how work practices are organized. In this dissertation, I present a design framework to improve the groupware design process for loosely coupled workgroups. The framework has three main parts that add a new layer of support to each of the three stages in the general groupware design process: data collection about the target work setting, analysis of the data, and system design based on the analysis results. The framework was developed to provide designers with support during each of these stages so that they can consider important characteristics of loosely coupled work practice while carrying out design for the target group. The design framework is based on information from CSCW and organizational research, and on real-world design experiences with one type of loosely coupled workgroup—home care treatment teams. The framework was evaluated using observations, interviews, and field trials that were carried out with multidisciplinary home care treatment teams in Saskatoon Health Region. A series of field observations and interviews were carried out with team members from each of the home care disciplines. The framework was then used to develop Mohoc, a groupware system that supports work in home care. Two field trials were carried out where the system was used by teams to support their daily activities. Results were analyzed to determine how well each part of the design framework performed in the design process. The results suggest that the framework was able to fill its role in specializing the general CSCW design process for loosely coupled groups by adding consideration for work and collaboration patterns that are seen in loosely coupled settings. However, further research is needed to determine whether these findings generalize to other loosely coupled workgroups

Personalized patient education and the internet : Linking health information to the Electronic Patient Record : STEPPS in burn care

Väitöskirja, sis. artikkelitSTEPPS = STructured Evaluated Personalized Patient Support = Rakenteinen, arvioitu ja yksilöllistetty potilastuk

Facilitating networks of information.

In this paper we describe an approach to respond to a request for information with the identification and location of the appropriate person as a source of information for answering the question. The expertise of a person is characterized using a weighted profile that has been derived from a series of documents describing the expert's activities. Having these profiles, requests for information can be matched with these profiles. The best matches correspond with the people that are experts for providing information on the request