Browsing by Author "Zhang, Qingquan"
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Item Benchmarking Machine Learning: How Fast Can Your Algorithms Go?(2021-01-08) Ning, Zeyu; Iradukunda, Hugues Nelson; Zhang, Qingquan; Zhu, TingThis paper is focused on evaluating the effect of some different techniques in machine learning speed-up, including vector caches, parallel execution, and so on. The following content will include some review of the previous approaches and our own experimental results.Item Benchmarking Resource Usage of Underlying Datatypes of Apache Spark(2020-12-08) Nicholls, Brittany; Adangwa, Mariama; Estes, Rachel; Iradukunda, Hugues Nelson; Zhang, Qingquan; Zhu, TingThe purpose of this paper is to examine how resource usage of an analytic is affected by the different underlying datatypes of Spark analytics - Resilient Distributed Datasets (RDDs), Datasets, and DataFrames. The resource usage of an analytic is explored as a viable, and preferred alternative of benchmarking big data analytics instead of the current common benchmarking performed using execution time. The run time of an analytic is shown to not be guaranteed to be a reproducible metric since many external factors to the job can affect the execution time. Instead, metrics readily available through Spark including peak execution memory are used to benchmark the resource usage of these different datatypes in common applications of Spark analytics, such as counting, caching, repartitioning, and KMeans.Item Chatbot Application on Cryptocurrency(IEEE, 2019-07-11) Xie, Qitao; Zhang, Qingquan; Tan, Dayuan; Zhu, Ting; Xiao, Shen; Li, Beibei; Sun, Lei; Yi, Ping; Wang, JunyuMany chatbots have been developed that provide a multitude of services through a wide range of methods. A chatbot is a brand-new conversational agent in the highspeed changing technology world. With the advance of Artificial Intelligence and machine learning, chatbots are becoming more and more popular. A chatbot is the extension of human interface mediums such as the phone and social platforms. Similarly, Cryptocurrency is a new extension of digital or virtual currency designed to work as a medium of exchange. In the current digital exchanging world, investors and interested parties are eager to know more information about, and the capabilites of, this new type of currency. One of the potential paths to retrieve the info automatically and quickly is through a chatbot. We explored the open source python library, Chatterbot, to apply Itchat API (a WeChat interface) with the aim of building a robot chatting application, I&C Chat, on the topic of cryptocurrency. First, we collected question and answer pairs datasets from Quora websites. Furthermore, we also created API calls to query the real time quote for the top 25 cryptocurrencies. Then we used the collected data to train our chatbot and implemented a logic adapter to receive the price quote of cryptocurrencies based on the incoming question. The Itchat API method will return the best matched answer to the asking party automatically. The response time of different questions has been investigated. The results imply that this application is quite useful, feasible and beneficial to the digital currency world.