Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Alexandros Labrinidis"'
Publikováno v:
The International FLAIRS Conference Proceedings. 35
Traditional recommender systems help users find the most relevant products or services to match their needs and preferences. However, they overlook the preferences of other sides of the market (aka stakeholders) involved in the system. In this paper,
Publikováno v:
ACM/IMS Transactions on Data Science. 1:1-33
Public transit is one of the first things that come to mind when someone talks about “smart cities.” As a result, many technologies, applications, and infrastructure have already been deployed to bring the promise of the smart city to public tran
Autor:
Alexandros Labrinidis, Kristi Bushman
Publikováno v:
Personal and Ubiquitous Computing. 26:781-794
The pervasiveness of public displays is prompting an increased need for “fresh” content to be shown, that is highly engaging and useful to passerbys. As such, live or time-sensitive content is often shown in conjunction with “traditional” sta
Publikováno v:
MDM
Recommender systems are widely used to help customers find the most relevant and personalized products or services tailored to their preferences. However, traditional systems ignore the preferences of the other side of the market, e.g., "product supp
Publikováno v:
ICDE Workshops
The increasing demand for real-time processing has contributed to the rapid evolution of Stream Processing Engines (SPEs). Low operational cost and timely delivery of results are important objectives, whose achievement relies on efficient load distri
Autor:
Mallory Avery, Robizon Khubulashvili, Kristi Bushman, Alexandros Labrinidis, Sera Linardi, Konstantinos Pelechrinis
Publikováno v:
SSRN Electronic Journal.
Publikováno v:
ICDE
Stream Processing Engines (SPEs) are used for realtime and continuous processing with stateful operations. This type of processing poses numerous challenges due to its associated complexity, unpredictable input, and need for timely results. As a resu
Publikováno v:
Proceedings of the VLDB Endowment. 10:1286-1297
Stream processing has become the dominant processing model for monitoring and real-time analytics. Modern Parallel Stream Processing Engines (pSPEs) have made it feasible to increase the performance in both monitoring and analytical queries by parall
Autor:
Kristi Bushman, Alexandros Labrinidis
Publikováno v:
PerDis
The pervasiveness of public displays is prompting an increased need for "fresh" content to be shown, that is highly engaging and useful to passerbys. As such, live or time-sensitive content is often shown in conjunction with "traditional" static cont
Publikováno v:
CODASPY
Data Stream Processing Systems (DSPSs) execute long-running, continuous queries over transient streaming data, often making use of outsourced, third-party computational platforms. However, third-party outsourcing can lead to unwanted violations of da