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1.
In this article we examine the complex relationship between care experience, mental health and exclusion from school and how young people (YP) negotiate these different experiences and identities. The study is a secondary analysis, informed by symbolic interactionist theory, of interviews conducted with 19 care experienced YP in Scotland. Not all of the YP were excluded and not all had a formal mental health diagnosis, as such our study design allows interrogation of the contexts and relationships which not only facilitate but also disrupt pathways to exclusion. It also allows reconsideration of assumptions of vulnerability which are often applied to care experienced YP. Our findings suggest that these YP are moving beyond ‘role playing’ the identities ascribed to them and actively seek out relationships which enable them to construct alternative identities.  相似文献   
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Although there has been a great deal of research into Collaborative Information Retrieval (CIR) and Collaborative Information Seeking (CIS), the majority has assumed that team members have the same level of unrestricted access to underlying information. However, observations from different domains (e.g. healthcare, business, etc.) have suggested that collaboration sometimes involves people with differing levels of access to underlying information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, no studies have been conducted to investigate the effect of awareness, an existing CIR/CIS concept, on MLCIR. To address this gap in current knowledge, we conducted two separate user studies using a total of 5 different collaborative search interfaces and 3 information access scenarios. A number of Information Retrieval (IR), CIS and CIR evaluation metrics, as well as questionnaires were used to compare the interfaces. Design interviews were also conducted after evaluations to obtain qualitative feedback from participants. Results suggested that query properties such as time spent on query, query popularity and query effectiveness could allow users to obtain information about team's search performance and implicitly suggest better queries without disclosing sensitive data. Besides, having access to a history of intersecting viewed, relevant and bookmarked documents could provide similar positive effect as query properties. Also, it was found that being able to easily identify different team members and their actions is important for users in MLCIR. Based on our findings, we provide important design recommendations to help develop new CIR and MLCIR interfaces.  相似文献   
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Quantum algorithms are a field of growing interest within the theoretical computer science as well as the physics community. Surprisingly, although the number of researchers working on the subject is ever-increasing, the number of quantum algorithms found so far is quite small. In fact, the task of designing new quantum algorithms has been proven to be extremely difficult. In this paper we give an overview of the known quantum algorithms and briefly describe the underlying ideas. Roughly, the algorithms presented are divided into hidden subgroup type algorithms and in amplitude amplification type algorithms. While the former deal with problems of group-theoretical nature and have the promise to yield strong separations of classical and quantum algorithms, the latter have been proved to be a prolific source of algorithms in which a polynomial speed-up as compared to classical algorithms can be achieved. We also discuss quantum algorithms which do not fall under these two categories and give a survey of techniques of general interest in quantum computing such as adiabatic computing, lower bounds for quantum algorithms, and quantum interactive proofs.  相似文献   
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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  相似文献   
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