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Titlebook: Web Information Systems Engineering – WISE 2016; 17th International C Wojciech Cellary,Mohamed F. Mokbel,Yanchun Zhang Conference proceedin

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發(fā)表于 2025-3-21 17:35:36 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Web Information Systems Engineering – WISE 2016
副標(biāo)題17th International C
編輯Wojciech Cellary,Mohamed F. Mokbel,Yanchun Zhang
視頻videohttp://file.papertrans.cn/1022/1021529/1021529.mp4
概述Includes supplementary material:
叢書(shū)名稱Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Web Information Systems Engineering – WISE 2016; 17th International C Wojciech Cellary,Mohamed F. Mokbel,Yanchun Zhang Conference proceedin
描述.This two volume set LNCS 10041 and LNCS 10042 constitutes the proceedings of the 17th International Conference on Web Information Systems Engineering, WISE 2016, held in Shanghai, China, in November 2016...The 39 full papers and 31 short papers presented in these proceedings were carefully reviewed and selected from 233 submissions. The papers cover a wide range of topics such as Social Network Data Analysis; Recommender Systems; Topic Modeling; Data Diversity; Data Similarity; Context-Aware Recommendation; Prediction; Big Data Processing; Cloud Computing; Event Detection; Data Mining; Sentiment Analysis; Ranking in Social Networks; Microblog Data Analysis; Query Processing; Spatial and Temporal Data; Graph Theory; Non-Traditional Environments; and Special Session on Data Quality and Trust in Big Data..
出版日期Conference proceedings 2016
關(guān)鍵詞big data; cloud computing; recommender systems; semantic Web; Web mining; complex networks; data mining; de
版次1
doihttps://doi.org/10.1007/978-3-319-48743-4
isbn_softcover978-3-319-48742-7
isbn_ebook978-3-319-48743-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing AG 2016
The information of publication is updating

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Dynamic Topic-Based Sentiment Analysis of Large-Scale Online Newso a generative topic model. Additionally, we further consider the links among news comments to avoid the error caused by user interactions. Finally, we derive distributed online inference procedures to update the model with newly arrived data and show the effectiveness of our proposed model on real-world data sets.
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POL: A Pattern Oriented Load-Shedding for Semantic Data Stream Processingg task through a unique pass, the approach extracts the exact needed semantic data from the stream. The conducted experiments on public available datasets have demonstrated the effectiveness of our approach.
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Partially Decompressing Binary Interpolative Coding for Fast Query Processingntal results on two publicly available standard corpora show that compared with normal IPC our algorithm performs 40?% faster for Boolean conjunctive queries and 20?% faster for Rank queries without additional storage consumption.
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Dynamic Topic-Based Sentiment Analysis of Large-Scale Online Newss on topic-based sentiment analysis of product reviews cannot be applied to online news directly because of the following two reasons: (1) The dynamic nature of news streams require the topic and sentiment analysis model also to be dynamically updated. (2) The user interactions among news comments c
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