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researchers learn quickly about a new field, such surveys are in a small amount and their formation cycles are long which will lead to delay. Therefore, tools and systems are urgently needed to automatically generate a comprehensive, detailed and accurate survey according to the given topic words ( Nenkova & McKeown, 2011 ). Here, survey means literature review. At the same time, such tools and systems should also help researchers retrieve relevant information in real time.
Ideally, automatic survey tools may deal with problems mentioned above. When applying such tools
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consumers, and thus strengthen their loyalty.
Interaction serves as one of the most prominent features of the online shopping environment. Online enterprises provide consumers with interactive tools that are conducive to attracting consumers’ attention and enable consumers to perceive and experience online shop interaction and enterprises ( Wu and Hsing, 2006 ). For average customers, it is nearly impossible to talk with B2C enterprises face to face. It is the interactive tools provided by B2C enterprises that play the role of the direct communicator. In B2C interaction
-opening developments. There are many new concepts, technologies, tools, and applications our students need to learn, such as MapReduce/Hadoop, Spark, NoSQL, NewSQL, in-memory computing, data virtualizations, big data warehousing, data lake, cloud computing, Internet of Things (IoT), artificial intelligence, robots communicating with human, virtual reality, augmented reality, machine learning, deep learning, cognitive computing, and big data analytics. These technologies contributed to the digital revolution with the development of many innovative applications in all sectors of
On Implicitly Discovered OLAP Schema-Specific Preferences in Reporting Tool
We propose content-based methods for construction of recommendations for reports in the OLAP reporting tool. Recommendations are generated based on preference information in user profile, which is updated implicitly by collecting and analyzing user activity in the reporting tool. Taking advantage of data about user preferences for data warehouse schema elements, existing reports that potentially may be interesting to the user are distinguished and recommended. The approach used for recommending reports is composed of two methods - cold-start and hot-start.