37 resultados para Palmer Search-expedition.


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Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

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Formal Concept Analysis is an unsupervised machine learning technique that has successfully been applied to document organisation by considering documents as objects and keywords as attributes. The basic algorithms of Formal Concept Analysis then allow an intelligent information retrieval system to cluster documents according to keyword views. This paper investigates the scalability of this idea. In particular we present the results of applying spatial data structures to large datasets in formal concept analysis. Our experiments are motivated by the application of the Formal Concept Analysis idea of a virtual filesystem [11,17,15]. In particular the libferris [1] Semantic File System. This paper presents customizations to an RD-Tree Generalized Index Search Tree based index structure to better support the application of Formal Concept Analysis to large data sources.

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Objective: To test the feasibility of an evidence-based clinical literature search service to help answer general practitioners' (GPs') clinical questions. Design: Two search services supplied GPs who submitted questions with the best available empirical evidence to answer these questions. The GPs provided feedback on the value of the service, and concordance of answers from the two search services was assessed. Setting: Two literature search services (Queensland and Victoria), operating for nine months from February 1999. Main outcome measures: Use of the service; time taken to locate answers; availability of evidence; value of the service to GPs; and consistency of answers from the two services. Results: 58 GPs asked 160 questions (29 asked one, 11 asked five or more). The questions concerned treatment (65%), aetiology (17%), prognosis (13%), and diagnosis (5%). Answering a question took a mean of 3 hours 32 minutes of personnel time (95% Cl, 2.67-3.97); nine questions took longer than 10 hours each to answer, the longest taking 23 hours 30 minutes. Evidence of suitable quality to provide a sound answer was available for 126 (79%) questions. Feedback data for 84 (53%) questions, provided by 42 GPs, showed that they appreciated the service, and asking the questions changed clinical care. There were many minor differences between the answers from the two centres, and substantial differences in the evidence found for 4/14 questions. However, conclusions reached were largely similar, with no or only minor differences for all questions. Conclusions: It is feasible to provide a literature search service, but further assessment is needed to establish its cost effectiveness.

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The rise of melanoma and the almost complete decline of stomach cancer clearly reflect disturbances of human culture during the 20th century. Environmental factors play a dominant role in the epidemiology of melanoma and many other malignancies.

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Most Internet search engines are keyword-based. They are not efficient for the queries where geographical location is important, such as finding hotels within an area or close to a place of interest. A natural interface for spatial searching is a map, which can be used not only to display locations of search results but also to assist forming search conditions. A map-based search engine requires a well-designed visual interface that is intuitive to use yet flexible and expressive enough to support various types of spatial queries as well as aspatial queries. Similar to hyperlinks for text and images in an HTML page, spatial objects in a map should support hyperlinks. Such an interface needs to be scalable with the size of the geographical regions and the number of websites it covers. In spite of handling typically a very large amount of spatial data, a map-based search interface should meet the expectation of fast response time for interactive applications. In this paper we discuss general requirements and the design for a new map-based web search interface, focusing on integration with the WWW and visual spatial query interface. A number of current and future research issues are discussed, and a prototype for the University of Queensland is presented. (C) 2001 Published by Elsevier Science Ltd.