In a document retrieval system where data is stored and compared with a specific query and then compared with other documents, we need to find the document that is most similar to the query. The most similar document will have the weight higher than other documents. When more than one document are proposed to the user, these documents have to be sorted according to their weights. Once the result is presented to the user by a recommender system, the user may check any document of interest. If there are two different documents’ lists, as two proposed results presented by different recommender systems, then, there is a need to find which list is more efficient. To do so, the measuring tool "Search Engine Ranking Efficiency Evaluation Tool [SEREET]" came to existence. This tool assesses the efficiency of each documents list and assigns a numerical value to the list. The value will be closer to 100% if the ranking list efficiency is high which means more relevance documents exist in the list and documents are sorted according to their relevance to the user.
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In a document retrieval system where data is stored and compared with a specific query and then compared with other documents, we need to find the document that is most similar to the query. The most similar document will have the weight higher than other documents. When more than one document are proposed to the user, these documents have to be sorted according to their weights. Once the result is presented to the user by a recommender system, the user may check any document of interest. If there are two different documents' lists, as two proposed results presented by different recommender systems, then, there is a need to find which list is more efficient. To do so, the measuring tool "Search Engine Ranking Efficiency Evaluation Tool [SEREET]" came to existence. This tool assesses the efficiency of each documents list and assigns a numerical value to the list. The value will be closer to 100% if the ranking list efficiency is high which means more relevance documents exist in the list and documents are sorted according to their relevance to the user.
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Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In a document retrieval system where data is storedand compared with a specific query and then comparedwith other documents, we need to find the documentthat is most similar to the query. The most similardocument will have the weight. Nº de ref. del artículo: 4958273
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In a document retrieval system where data is storedand compared with a specific query and then comparedwith other documents, we need to find the documentthat is most similar to the query. The most similardocument will have the weight higher than otherdocuments. When more than one document are proposedto the user, these documents have to be sortedaccording to their weights. Once the result ispresented to the user by a recommender system, theuser may check any document of interest. If there aretwo different documents lists, as two proposedresults presented by different recommender systems,then, there is a need to find which list is moreefficient. To do so, the measuring tool SearchEngine Ranking Efficiency Evaluation Tool [SEREET] came to existence. This tool assesses the efficiencyof each documents list and assigns a numerical valueto the list. The value will be closer to 100% if theranking list efficiency is high which means morerelevance documents exist in the list and documentsare sorted according to their relevance to the user. Nº de ref. del artículo: 9783639109443
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Taschenbuch. Condición: Neu. Induction-Based Approach to Personalized Search Engines | Introducing The Search Engines Ranking Efficiency Evaluation Tool [SEREET] | Wadee Halabi | Taschenbuch | Kartoniert / Broschiert | Englisch | 2013 | VDM Verlag Dr. Müller | EAN 9783639109443 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. Nº de ref. del artículo: 101680097
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