1000 resultados para Royal York Hotel


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Standing l-r: George? son of Max Reiss?, Max Reiss, Harry Gould, Moritz Reiss, Joe Reiss, and Herbert Reiss; Seated l-r: Trude Reiss (wife of Herbert), Else Reiss (mother of Joe), Lily Friedlander Gould, Eva Fantl Gould, Trude Reiss (wife of Joe), and Marta Reiss (wife of Max)

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Standing l-r: George? son of Max Reiss?, Max Reiss, Harry Gould, Moritz Reiss, Joe Reiss, and Herbert Reiss; Seated l-r: Trude Reiss (wife of Herbert), Else Reiss (mother of Joe), Lily Friedlander Gould, Eva Fantl Gould, Trude Reiss (wife of Joe), and Marta Reiss (wife of Max)

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Boberach: Die Überwindung der Folgen der Revolution von 1848 ist den Reformen nach 1806 zu vergleichen

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This publication captures the outputs of a JISC infoNet conference held in February 2004 in the Royal York Hotel, York. The event was entitled ‘When Worlds Collide’ because it aimed to explore the cultural differences between the different communities involved in developing and supporting learning environments hence the event was promoted in collaboration with ALT and UCISA. We defined learning environment in the broadest sense to encompass all of the structures, systems and processes that impact on the learning experience. For many this is summed up in the term Managed Learning Environment (MLE) although others favour alternative terminologies. The event was thus unusual in that it brought together people, from learning and teaching, MIS, library, administrative and senior management backgrounds, that don’t often get the opportunity to network with one another.

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A jewelry case which is a souvenir of the opening of the Royal York Hotel, June 1929. The case is faux leather with a velveteen lining. Inside the case is a pin for the Daughers' of the Empire. The pin belonged to Margaret Julia Woodruff (Band). "Margaret Woodruff" is scratched onto the back of the pin. She joined the group in 1909.

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Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.

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This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

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Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

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commissioned by Ballet Rambert for 60th Anniversary season, choreographer Mary Evelyn, designer Liz Emmanuel. World premiere: Theatre Royal York 03/06/86

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A photograph of the Right Hon. John J. Diefenbaker with Sean O'Sullivan. The photograph is labelled on the reverse: "With the Right Hon. John J. Diefenbaker, 1965, Royal Connaught Hotel, Hamilton". Sean O'Sullivan would have been 13 years old at the time of the photograph.

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The King’s Royal Regiment of New York was a Loyalist regiment that served on the Canadian frontier during the American Revolutionary War. The regiment was commanded by Sir John Johnson, who recruited members from the settlers on his estates in the Mohawk Valley. After the War, the two battalions of the regiment were disbanded. The First Battalion settled on the north shore of the St. Lawrence, while the Second Battalion settled by the Bay of Quinte.