Titlebook: Collaborate Computing: Networking, Applications and Worksharing; 12th International C Shangguang Wang,Ao Zhou Conference proceedings 2017 I

mortality

書目名稱Collaborate Computing: Networking, Applications and Worksharing影響因子(影響力)




書目名稱Collaborate Computing: Networking, Applications and Worksharing影響因子(影響力)學(xué)科排名




書目名稱Collaborate Computing: Networking, Applications and Worksharing網(wǎng)絡(luò)公開(kāi)度




書目名稱Collaborate Computing: Networking, Applications and Worksharing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Collaborate Computing: Networking, Applications and Worksharing被引頻次




書目名稱Collaborate Computing: Networking, Applications and Worksharing被引頻次學(xué)科排名




書目名稱Collaborate Computing: Networking, Applications and Worksharing年度引用




書目名稱Collaborate Computing: Networking, Applications and Worksharing年度引用學(xué)科排名




書目名稱Collaborate Computing: Networking, Applications and Worksharing讀者反饋




書目名稱Collaborate Computing: Networking, Applications and Worksharing讀者反饋學(xué)科排名

慌張

承認(rèn)

Parallel Seed Selection for Influence Maximization Based on ,-, Decompositionolutions, the greedy and its improvements are time-consuming. In this paper, we propose candidate shells influence maximization (.) algorithm under heat diffusion model to select seeds in parallel. We employ . algorithm (a modified algorithm of greedy) to coarsely estimate the influence spread to av

休閑

The Service Recommendation Problem: An Overview of Traditional and Recent Approachesand more important for describing non-functional characteristics of services. The most popular technique is the Collaborative Filtering (CF) based on QoS values. Existing few approaches for service recommendation based on CF have been studied, so we are going to do a survey of these techniques in de

包裹

Gaussian LDA and Word Embedding for Semantic Sparse Web Service Discoverytuation, users rely heavily on the search engine model to retrieve their expected Web services. However, due to the fact that Web services registered in API marketplaces are described in short texts, the search engine based discovery method suffers from the semantic sparsity problem, which in turn l

enlist

Quality-Assure and Budget-Aware Task Assignment for Spatial Crowdsourcing research among academic and industry community. As participants may possess different capabilities and reliabilities, as well as the changeable locations and available time slots of both tasks and potential workers, a major challenge is how to assign spatial tasks to appropriate workers from lots o

enlist

Collaborative Prediction Model of Disease Risk by Mining Electronic Health Recordsgitudinal properties make EHRs analysis an inherently challenge. To address this issue, this paper proposes CAPM, a Collaborative Assessment Prediction Model based on patient temporal graph representation, which relies only on a patient EHRs using ICD-10 codes to predict future disease risks. Firstl

Dysarthria

An Adaptive Multiple Order Context Huffman Compression Algorithm Based on Markov Modelis traversed, and the character space of the data and the times that one character transfers to its neighboring character are figured out. According to the statistical results, we can calculate the one-step transition probability matrix and the multi-step transition probability matrix. When the cond

Texture

Course Relatedness Based on Concept Graph ModelingHowever, there are few researchers that concentrate on mining the relationship between courses. In this paper, we propose a method to compare relatedness between courses based on representing courses as concept graphs. The concept graph comprises not only the semantic relationship between concepts b

打包

Rating Personalization Improves Accuracy: A Proportion-Based Baseline Estimate Model for Collaboratind users. However, it doesn’t consider different users’ rating criterions and results in predictions may be out of recommendation’s rating range. In this paper, we propose a novel baseline estimate model to improve the current performance, named PBEModel (Proportion-based Baseline Estimate Model), w