The goal of Approximate Query Processing (AQP) is to provide very fast but "accurate enough" results for costly aggregate queries thereby improving user experience in interactive exploration large datasets. Recently proposed Machine-Learning based AQP techniques can low latency as query execution only involves model inference compared traditional processing on database clusters. However, with i...

Edge computing can reduce the transmission pressure of wireless networks in earthquakes by pushing functionalities to network edges and avoiding data cloud servers. However, this also leads scattered storage content each edge server, increasing difficulty search. This paper investigates seismic query problem supported computing. We first design a lookup mechanism based on bloom filter, which qu...

Conventional membership inference attacks usually require a large number of queries the target model when training shadow models, and this task becomes extremely difficult is limited. Aiming at problem insufficient data for models due to limited queries, we propose attack method based on generative adversarial networks (GAN). First, use augment samples obtained by small expand model; Secondly, ...

Due to the increasing web, there are many challenges to establish a general framework for data mining and retrieving structured data from the Web. Creating an ontology is a step towards solving this problem. The ontology raises the main entity and the concept of any data in data mining. In this paper, we tried to propose a method for applying the "meaning" of the search system, But the problem ...

the main challenge of a search engine is ranking web documents to provide the best response to a user`s query. despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. in this paper, a ranking algorithm based on the reinforcement le...