Report title：CurrentClean: Spatio-temporal Cleaning of Stale seabet
Report time：2019Year11month7Sunday afternoon3：00
Reporting location：Central South seabetseabet Main Computer Building308Conference Room
Reporter：Zheng seabet (seabet seabet)
Report Summary：seabet currency is imperative towards achieving up-to-date and accurate seabet analysis. seabet is considered current if changes in real world entities are reflected in the database. When this does not occur, stale seabet arises. Identifying and repairing stale seabet goes beyond simply having timestamps. Individual entities each have their own update patterns in both space and time, e.g., each bank client has her own deposit/withdrawal patterns that influence whether her account balance is up-to-date, irrespective of the last update time. These update patterns can be learned and predicted given available query logs. In this paper, we present CurrentClean, a probabilistic system for identifying and cleaning stale values. We introduce a spatio-temporal probabilistic model that captures the database update patterns to infer stale values, and propose a set of inference rules that model spatio-temporal update patterns commonly seen in real seabet. We recommend repairs to clean stale values by learning from past update values over cells to repair stale values to current values. Our evaluation shows CurrentClean's effectiveness to identify stale values over real seabet, and achieves improved error detection and repair accuracy over state-of-the-art techniques.
About the speaker：Zheng Zheng，PhD candidate in seabet of Computer Science, McMaster University, Canada。2015Received a master's degree in computer science from the seabet of Chinese Academy of Sciences，His research field is: database system，Big seabet management，Machine Learning。atICDE、CIKM、EDBT、Transactions in GISPublished many academic papers in important international journals and conferences.
