中國計(jì)算機(jī)學(xué)會(huì)(CCF)日前完成了《中國計(jì)算機(jī)學(xué)會(huì)推薦國際學(xué)術(shù)會(huì)議和期刊目錄》第六版的審定,。Data Science and Engineering(DSE)期刊經(jīng)過評審在新版目錄上被推薦為“數(shù)據(jù)庫/數(shù)據(jù)挖掘/內(nèi)容檢索”領(lǐng)域C類期刊,。
中國計(jì)算機(jī)學(xué)會(huì)推薦國際學(xué)術(shù)會(huì)議和期刊目錄作為國內(nèi)影響力廣泛的推薦目錄,其遴選標(biāo)準(zhǔn)及程序十分嚴(yán)格,。此次入選表明:DSE在學(xué)術(shù)水平和期刊出版標(biāo)準(zhǔn)化,、規(guī)范化等方面均得到了CCF的認(rèn)可,這對進(jìn)一步提升期刊的學(xué)術(shù)影響力具有重要意義,。
在此,,DSE向?yàn)槠诳l(fā)展作出巨大貢獻(xiàn)的主編、編委,、客座編輯,、審稿專家、作者們和贊助商南京中新賽克科技有限責(zé)任公司(Sinovatio)表示衷心的感謝,,也向關(guān)注期刊發(fā)展的廣大讀者表示誠摯的謝意,!DSE會(huì)繼續(xù)秉承高質(zhì)量的辦刊原則,為廣大科研工作者提供更優(yōu)秀的學(xué)術(shù)研究成果和更專業(yè)的出版服務(wù),,重點(diǎn)向國內(nèi)外同行推介數(shù)據(jù)科學(xué)與工程領(lǐng)域最新最前沿的研究成果,,為國內(nèi)國際數(shù)據(jù)科學(xué)與工程領(lǐng)域同行提供一個(gè)互動(dòng)交流的空間,提升中國數(shù)據(jù)庫學(xué)科在國際學(xué)術(shù)界的競爭力和影響力,。歡迎大家踴躍投稿!
期刊簡介
Data Science and Engineering(DSE)是由中國計(jì)算機(jī)學(xué)會(huì)主辦,,數(shù)據(jù)庫專業(yè)委員會(huì)承辦,,施普林格·自然(Springer Nature)出版的開放獲?。∣pen Access)期刊。DSE致力于發(fā)表與數(shù)據(jù)科學(xué)與工程領(lǐng)域相關(guān)的關(guān)鍵科學(xué)問題與前沿研究熱點(diǎn),,以大數(shù)據(jù)為研究重點(diǎn),,建設(shè)國際學(xué)術(shù)交流的重要平臺,推動(dòng)學(xué)術(shù)界和企業(yè)界的深度融合,。征稿范疇主要包括:大數(shù)據(jù)管理,、大數(shù)據(jù)處理、大數(shù)據(jù)分析,、大數(shù)據(jù)治理等相關(guān)基礎(chǔ)理論,、關(guān)鍵技術(shù)與系統(tǒng)實(shí)踐。現(xiàn)任主編(Editors-in-Chief)為數(shù)據(jù)科學(xué)與工程領(lǐng)域的知名專家北京大學(xué)崔斌教授和希臘雅典娜研究中心Timos Sellis教授,,現(xiàn)任執(zhí)行主編(Managing Editor)為數(shù)據(jù)庫專業(yè)委員會(huì)主任李戰(zhàn)懷教授,。
DSE的主要特色優(yōu)勢包括:● CCF重點(diǎn)發(fā)展的學(xué)術(shù)期刊,入選全國學(xué)會(huì)期刊出版能力提升計(jì)劃,、被推薦為CCF-C類期刊● 已被EI,、ESCI、SCOPUS等國際知名數(shù)據(jù)庫收錄,。期刊即時(shí)CiteScore引用分為8.6,,2021年度CiteScore為6.4,較2020年的4.9分別增長75.5%與30.6%,。期刊2022年全文下載高達(dá)175,497次● 開放獲?。?/span>Open Access)期刊,高曝光度,,由贊助商贊助出版費(fèi),,快速發(fā)表。
DSE主頁:https://www.springer.com/journal/41019
2021,、2022年熱點(diǎn)論文推薦
1. Peng, Y., Choi, B. & Xu, J. Graph Learning for Combinatorial Optimization: A Survey of State-of-the-Art(面向組合優(yōu)化問題的圖學(xué)習(xí)綜述). Data Sci. Eng. 6, 119–141 (2021).
https://doi.org/10.1007/s41019-021-00155-3
2. Sarki, R., Ahmed, K., Wang, H. et al. Image Preprocessing in Classification and Identification of Diabetic Eye Diseases(面向糖尿病型眼疾分類和識別的圖像預(yù)處理方法). Data Sci. Eng. 6, 455–471 (2021).
https://doi.org/10.1007/s41019-021-00167-z
3. Mahajan, R., Mansotra, V. Predicting Geolocation of Tweets: Using Combination of CNN and BiLSTM(結(jié)合CNN和BiLSTM的推文地理位置預(yù)測方法). Data Sci. Eng. 6, 402–410 (2021).
https://doi.org/10.1007/s41019-021-00165-1
4. Yang, J., Yao, W. & Zhang, W. Keyword Search on Large Graphs: A Survey(大規(guī)模圖數(shù)據(jù)上的關(guān)鍵詞搜索綜述). Data Sci. Eng. 6, 142–162 (2021).
https://doi.org/10.1007/s41019-021-00154-4
5. Liu, J., Shao, Y. & Su, S. Multiple Local Community Detection via High-Quality Seed Identification over Both Static and Dynamic Networks(面向靜態(tài)和動(dòng)態(tài)網(wǎng)絡(luò)的基于高質(zhì)量種子識別的多重局部社區(qū)發(fā)現(xiàn)). Data Sci. Eng. 6, 249–264 (2021).
https://doi.org/10.1007/s41019-021-00160-6
6. Abburi, H., Parikh, P., Chhaya, N. et al. Fine-Grained Multi-label Sexism Classification Using a Semi-Supervised Multi-level Neural Approach(基于半監(jiān)督多層神經(jīng)網(wǎng)絡(luò)的細(xì)粒度多標(biāo)簽性別歧視分類). Data Sci. Eng. 6, 359–379 (2021).
https://doi.org/10.1007/s41019-021-00168-y
7. Zhao, Y., Hu, Y., Yuan, P. et al. Maximizing Influence Over Streaming Graphs with Query Sequence(面向流圖的基于查詢序列的影響力最大化方法). Data Sci. Eng. 6, 339–357 (2021).
https://doi.org/10.1007/s41019-021-00158-0
8. Wu, Y., Zhao, J., Sun, R. et al. Efficient Personalized Influential Community Search in Large Networks(大型網(wǎng)絡(luò)中最大個(gè)性化影響力社群的高效搜索研究). Data Sci. Eng. 6, 310–322 (2021).
https://doi.org/10.1007/s41019-021-00163-3
9. Dai, S., Yu, Y., Fan, H. et al. Spatio-Temporal Representation Learning with Social Tie for Personalized POI Recommendation(面向個(gè)性化 POI 推薦的結(jié)合社交關(guān)系的時(shí)空表示學(xué)習(xí)研究). Data Sci. Eng. 7, 44–56 (2022).
https://doi.org/10.1007/s41019-022-00180-w
10. Ha, M., Shichkina, Y. Translating a Distributed Relational Database to a Document Database(分布式關(guān)系數(shù)據(jù)庫到文檔數(shù)據(jù)庫的轉(zhuǎn)換研究). Data Sci. Eng. 7, 136–155 (2022).
https://doi.org/10.1007/s41019-022-00181-9
11. Davoudian, A., Chen, L., Tu, H. et al. A Workload-Adaptive Streaming Partitioner for Distributed Graph Stores(面向分布式圖數(shù)據(jù)存儲(chǔ)的工作負(fù)載自適應(yīng)流數(shù)據(jù)分區(qū)器). Data Sci. Eng. 6, 163–179 (2021).
12. Ge, YF., Cao, J., Wang, H. et al. Set-Based Adaptive Distributed Differential Evolution for Anonymity-Driven Database Fragmentation(面向匿名驅(qū)動(dòng)數(shù)據(jù)庫分片的基于集合的自適應(yīng)分布式差分進(jìn)化算法). Data Sci. Eng. 6, 380–391 (2021).
https://doi.org/10.1007/s41019-021-00170-4
13. Liu, P., Wang, M., Cui, J. et al. Top-k Competitive Location Selection over Moving Objects(面向移動(dòng)對象的Top-k競爭位置選擇算法). Data Sci. Eng. 6, 392–401 (2021).
https://doi.org/10.1007/s41019-021-00157-1
14. Mondal, A., Kakkar, A., Padhariya, N. et al. Efficient Indexing of Top-k Entities in Systems of Engagement with Extensions for Geo-tagged Entities(面向擴(kuò)展地理標(biāo)記實(shí)體的參與型系統(tǒng)中Top-k實(shí)體的高效索引研究). Data Sci. Eng. 6, 411–433 (2021).
https://doi.org/10.1007/s41019-021-00173-1
15. Zhao, X., Zeng, W., Tang, J. et al. Toward Entity Alignment in the Open World: An Unsupervised Approach with Confidence Modeling(開放世界假設(shè)下的實(shí)體對齊研究:基于置信度建模的無監(jiān)督方法). Data Sci. Eng. 7, 16–29 (2022).
https://doi.org/10.1007/s41019-022-00178-4
16. Zhu, H., Li, W., Liu, W. et al. Top k Optimal Sequenced Route Query with POI Preferences(POI偏好感知的Top-k最優(yōu)序列路線查詢). Data Sci. Eng. 7, 3–15 (2022).
https://doi.org/10.1007/s41019-022-00177-5
17. Khope, S.R., Elias, S. Critical Correlation of Predictors for an Efficient Risk Prediction Framework of ICU Patient Using Correlation and Transformation of MIMIC-III Dataset(基于MIMIC-III數(shù)據(jù)集相關(guān)性與轉(zhuǎn)換的ICU患者高效風(fēng)險(xiǎn)預(yù)測框架的預(yù)測因子的關(guān)鍵相關(guān)性研究). Data Sci. Eng. 7, 71–86 (2022).
https://doi.org/10.1007/s41019-022-00176-6
18. Luo, J., Xiao, S., Jiang, S. et al. ripple2vec: Node Embedding with Ripple Distance of Structures(ripple2vec:基于結(jié)構(gòu)波紋距離的節(jié)點(diǎn)嵌入研究). Data Sci. Eng. 7, 156–174 (2022).
https://doi.org/10.1007/s41019-022-00184-6
19. Bagozi, A., Bianchini, D. & Antonellis, V.D. Context-Based Resilience in Cyber-Physical Production System(信息物理生產(chǎn)系統(tǒng)中基于情境的恢復(fù)力研究). Data Sci. Eng. 6, 434–454 (2021).
https://doi.org/10.1007/s41019-021-00172-2
20. P, D., Abraham, S.S. FairLOF: Fairness in Outlier Detection(FairLOF:離群點(diǎn)檢測中的公平性研究). Data Sci. Eng. 6, 485–499 (2021).
https://doi.org/10.1007/s41019-021-00169-x