‘The feeling of exclusion’: Young peoples' perceptions of art galleries

This article first looks at the relationship between museums and art galleries and their potential audiences and, in particular, the under-represented sector of young visitors. It examines the main findings from the limited research available on young visitors, and goes on to discuss theories delineating the differences between the cultures, identities and values of culture consumers and culture providers. The second part of the article looks at what specific museums have done towards being more inclusive in their appeal, and then reports the findings of a survey of young people in relation to New Zealand's Auckland Art Gallery. The survey found that young people's ideas of what constitutes modern, relevant art do not match standard art criteria, and that most exhibitions and marketing methods do not mesh with their worldview. The article concludes by using data from the survey to suggest ways of engaging more young people with public art galleries.     

Communicating Prevention: The Effects of the keepin' it REAL Classroom Videotapes and Televised PSAs on Middle-School Students' Substance Use

This study sought to determine if exposure to two communication-oriented activities, videotapes and public service announcements, accounts for changes in substance use among adolescents participating in the Drug Resistance Strategies Project's keepin' it REAL adolescent substance use prevention curriculum. Middle-school students (4,734, 72% Latino) responded to questionnaires related to these analyses. An analysis of covariance (ANCOVA) model was fit separately to six substance use outcomes. The results suggested that intervention students who saw four or five videos engaged in less substance use in the past month than did students who saw fewer videos. Having seen the PSAs one or more times did not predict the reported change in substance use.     

Quality and relevance of domain-specific search: A case study in mental health

When searching for health information, results quality can be judged against available scientific evidence: Do search engines return advice consistent with evidence based medicine? We compared the performance of domain-specific health and depression search engines against a general-purpose engine (Google) on both relevance of results and quality of advice. Over 101 queries, to which the term ‘depression’ was added if not already present, Google returned more relevant results than those of the domain-specific engines. However, over the 50 treatment-related queries, Google returned 70 pages recommending for or against a well studied treatment, of which 19 strongly disagreed with the scientific evidence. A domain-specific index of 4 sites selected by domain experts was only wrong in 5 of 50 recommendations. Analysis suggests a tension between relevance and quality. Indexing more pages can give a greater number of relevant results, but selective inclusion can give better quality.     

Hierarchical clustering of a Finnish newspaper article collection with graded relevance assessments

Search facilitated with agglomerative hierarchical clustering methods was studied in a collection of Finnish newspaper articles (N = 53,893). To allow quick experiments, clustering was applied to a sample (N = 5,000) that was reduced with principal components analysis. The dendrograms were heuristically cut to find an optimal partition, whose clusters were compared with each of the 30 queries to retrieve the best-matching cluster. The four-level relevance assessment was collapsed into a binary one by (A) considering all the relevant and (B) only the highly relevant documents relevant, respectively. Single linkage (SL) was the worst method. It created many tiny clusters, and, consequently, searches enabled with it had high precision and low recall. The complete linkage (CL), average linkage (AL), and Ward's methods (WM) returned reasonably-sized clusters typically of 18–32 documents. Their recall (A: 27–52%, B: 50–82%) and precision (A: 83–90%, B: 18–21%) was higher than and comparable to those of the SL clusters, respectively. The AL and WM clustering had 1–8% better effectiveness than nearest neighbor searching (NN), and SL and CL were 1–9% less efficient that NN. However, the differences were statistically insignificant. When evaluated with the liberal assessment A, the results suggest that the AL and WM clustering offer better retrieval ability than NN. Assessment B renders the AL and WM clustering better than NN, when recall is considered more important than precision. The results imply that collections in the highly inflectional and agglutinative languages, such as Finnish, may be clustered as the collections in English, provided that documents are appropriately preprocessed.     

Can constrained relevance feedback and display strategies help users retrieve items on mobile devices?

Searching online information resources using mobile devices is affected by small screens which can display only a fraction of ranked search results. In this paper we investigate whether the search effort can be reduced by means of a simple user feedback: for a screenful of search results the user is encouraged to indicate a single most relevant document. In our approach we exploit the fact that, for small display sizes and limited user actions, we can construct a user decision tree representing all possible outcomes of the user interaction with the system. Examining the trees we can compute an upper limit on relevance feedback performance. In this study we consider three standard feedback algorithms: Rocchio, Robertson/Sparck-Jones (RSJ) and a Bayesian algorithm. We evaluate them in conjunction with two strategies for presenting search results: a document ranking that attempts to maximize information gain from the user’s choices and the top-D ranked documents. Experimental results indicate that for RSJ feedback which involves an explicit feature selection policy, the greedy top-D display is more appropriate. For the other two algorithms, the exploratory display that maximizes information gain produces better results. We conducted a user study to compare the performance of the relevance feedback methods with real users and compare the results with the findings from the tree analysis. This comparison between the simulations and real user behaviour indicates that the Bayesian algorithm, coupled with the sampled display, is the most effective. Extended version of “Evaluating Relevance Feedback Algorithms for Searching on Small Displays, ” Vishwa Vinay, Ingemar J. Cox, Natasa Milic-Frayling, Ken Wood published in the proceedings of ECIR 2005, David E. Losada, Juan M. Fernández-Luna (Eds.), Springer 2005, ISBN 3-540-25295-9     

Another Look at What Moves Public Opinion: Media Agenda Setting and Polls in the 2000 U.S. Election

This study examined two levels of media agenda effects on aggregatepublic opinion from different news sources. The effects wereinvestigated immediately and cumulatively. Content analysisdata from the 2000 U.S. presidential election coverage by fournational news organizations were related to the Gallup pre-electionpoll standings of each candidate. Regression analyses foundthat both the salience of a candidate and the salience of theattributes of a candidate cumulatively, but not immediately,influenced his standing in the polls. An analysis of news sourcessupported the finding that the two levels of agenda-settingeffects seemed mostly cumulative rather than immediate. Newsfrom different sources, however, tended to have effects of differentdegrees and sometimes different directions on candidate pollstandings. Cumulative effects of candidate salience on aggregateopinion change were found for non-partisan and neutral newssources—reporters, poll reporting and public documents—whereasthe effects of candidate attribute salience mostly came frompartisan sources—the candidate himself and members ofthe competing political party. Possible political implicationsof these findings are discussed.     

Indianapolis I3: the third generation Integrated Advanced Information Management Systems.

In 2001, the Regenstrief Institute for Health Care and the Indiana University School of Medicine (IUSM) began an IAIMS planning effort to create a vision and a tactical plan for the first Integrated Advanced Information Management Systems (IAIMS) implementation to cross a large area and include unaffiliated institutions. A number of elements made this planning effort unique. Among these elements were the existence of a network infrastructure that supported the Indianapolis Network for Patient Care, the existence of a mature medical informatics program at the Regenstrief Institute, and the existence of a wide-area knowledge network fostered by the IUSM libraries. However, the leadership for a strong information technology role in the IUSM that could promote collaboration in support of education and research across the diverse Indianapolis hospital systems had been lacking. By bringing together various groups, each with a commitment to improve health care quality and public health across the Indianapolis metropolitan area, regardless of individual institutional affiliation, the strategic directions for I3-Indianapolis IAIMS Initiative have been defined and the foundations for a third generation IAIMS construct have been laid in Indianapolis, Indiana.     

Web usage mining at an academic health sciences library: an exploratory study.

OBJECTIVES: This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website. METHODS: Usage of database-driven resource gateway pages was logged for a six-month period, including information about users' network addresses, referring uniform resource locators (URLs), and types of resource accessed. RESULTS: It was found that referring URL did vary significantly by two factors: whether a user was on-campus and what type of resource was accessed. CONCLUSIONS: Although the data available for analysis are limited by the nature of the Web and concerns for privacy, this method demonstrates the potential for gaining insight into Web usage that supplements Web log analysis. It can be used to improve the design of static and dynamic Websites today and could be used in the design of more advanced Web systems in the future.     

Grundlagen des Burrows-Wheeler-Kompressionsalgorithmus

Der Burrows-Wheeler-Kompressionsalgorithmus hat als ein universelles Kompressionsverfahren in den letzten Jahren aufgrund seiner hervorragenden Kompressionsraten und hohen Verarbeitungsgeschwindigkeiten eine bemerkenswerte Beachtung erfahren. Das Herzstück des Algorithmus stellt die sogenannte Burrows-Wheeler-Transformation dar. Es handelt sich bei dieser Transformation um eine Permutation der Eingabedaten, welche Zeichen mit ähnlichem Kontext nahe beieinander anordnet. Die Transformation sowie die zugehörige Rücktransformation werden zusammen mit den weiteren Stufen des Algorithmus in einer gegenüber der Standardversion verbesserten Variante vorgestellt und die Ergebnisse mit denen anderer Datenkompressionsalgorithmen verglichen.