Titlebook: Data Mining and Big Data; Second International Ying Tan,Hideyuki Takagi,Yuhui Shi Conference proceedings 2017 Springer International Publis

ODDS

書目名稱Data Mining and Big Data影響因子(影響力)




書目名稱Data Mining and Big Data影響因子(影響力)學科排名




書目名稱Data Mining and Big Data網(wǎng)絡(luò)公開度




書目名稱Data Mining and Big Data網(wǎng)絡(luò)公開度學科排名




書目名稱Data Mining and Big Data被引頻次




書目名稱Data Mining and Big Data被引頻次學科排名




書目名稱Data Mining and Big Data年度引用




書目名稱Data Mining and Big Data年度引用學科排名




書目名稱Data Mining and Big Data讀者反饋




書目名稱Data Mining and Big Data讀者反饋學科排名

COW

Mining Relationship Between User Purposes and Product Features Towards Purpose-Oriented Recommendatimade by other users, which is not an effective way when confronting loaded of information and especially if the buyers are beginner users who have limited experience and knowledge. To deal with these problems, we propose a framework of purpose-oriented recommendation which present a ranking of produ

浪費物質(zhì)

Finding Top-k Fuzzy Frequent Itemsets from DatabasesNevertheless, frequent itemsets are redundant for the users. A better way is to show the top-k results accordingly. In this paper, we define the score of fuzzy frequent itemset and propose the problem of top-k fuzzy frequent itemset mining, which, to the best of our knowledge, has never been focused

精密

conscience

寡頭政治

Correlation Analysis of Diesel Engine Performance Testing Data Based on Mixed-Copula Methodring the diesel engine performance testing process including many control parameters which are strongly coupled with each other, it is difficult to carry out accurate probability distribution description and correlation analysis, this paper presents a correlation analysis method based on mixed copul

寡頭政治

Incorporate

Incremental Adaptive Time Series Prediction for Power Demand Forecastinge in grid and related costs. Our forecasting method is designed to process continuous stream of data from smart meters incrementally and to adapt the prediction model to concept drifts in power demand. It identifies drifts using a condition based on an acceptable distributor’s daily imbalance. Using

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