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Titlebook: Advances in Information Retrieval; 37th European Confer Allan Hanbury,Gabriella Kazai,Norbert Fuhr Conference proceedings 2015 Springer Int

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發(fā)表于 2025-3-21 19:23:37 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advances in Information Retrieval
期刊簡(jiǎn)稱37th European Confer
影響因子2023Allan Hanbury,Gabriella Kazai,Norbert Fuhr
視頻videohttp://file.papertrans.cn/149/148364/148364.mp4
學(xué)科分類Lecture Notes in Computer Science
圖書封面Titlebook: Advances in Information Retrieval; 37th European Confer Allan Hanbury,Gabriella Kazai,Norbert Fuhr Conference proceedings 2015 Springer Int
影響因子This book constitutes the proceedings of the 37th European Conference on IR Research, ECIR 2015, held in Vienna, Austria, in March/April 2015. The 44 full papers, 41 poster papers and 7 demonstrations presented together with 3 keynotes in this volume were carefully reviewed and selected from 305 submissions. The focus of the papers were on following topics: aggregated search and diversity, classification, cross-lingual and discourse, efficiency, evaluation, event mining and summarisation, information extraction, recommender systems, semantic and graph-based models, sentiment and opinion, social media, specific search tasks, temporal models and features, topic and document models, user behavior and reproducible IR.
Pindex Conference proceedings 2015
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Marina P. Antoch,Roman V. Kondratovlem. It finds the best position for all paragraphs, such that some articles consist mainly of distinct paragraphs and others consist mainly of duplicates. Finally, we present to the reader the articles with more distinct paragraphs. Our experiments show the high precision and recall of our approach.
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0302-9743 5. The 44 full papers, 41 poster papers and 7 demonstrations presented together with 3 keynotes in this volume were carefully reviewed and selected from 305 submissions. The focus of the papers were on following topics: aggregated search and diversity, classification, cross-lingual and discourse, ef
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Jay C. Dunlap,Jennifer J. Lorostion analysis (KCCA). In the second phase, correlated space centroids are obtained using clustering to retrieve cross-modal documents with different similarity measures. Experimental results show that C.SUR outperforms the existing state-of-the-art English cross-modal retrieval approaches and achieve similar results for other languages.
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