Weiguo Fan mainly investigates Information retrieval, Artificial intelligence, Marketing, Ranking and Machine learning. He has included themes like Web page, World Wide Web and Data mining in his Information retrieval study. His work on Information needs is typically connected to Service provider as part of general World Wide Web study, connecting several disciplines of science.
As a member of one scientific family, Weiguo Fan mostly works in the field of Artificial intelligence, focusing on Pattern recognition and, on occasion, Content-based image retrieval and Feature detection. The concepts of his Marketing study are interwoven with issues in Page view and Social media analytics. In Ranking, Weiguo Fan works on issues like Ranking, which are connected to Graph and Link analysis.
His primary scientific interests are in Information retrieval, Artificial intelligence, World Wide Web, Data mining and Machine learning. His Information retrieval study frequently involves adjacent topics like Ranking. The study incorporates disciplines such as Natural language processing and Pattern recognition in addition to Artificial intelligence.
World Wide Web is closely attributed to Key in his work. Weiguo Fan has researched Genetic programming in several fields, including Genetic algorithm and Visual Word, Image retrieval, Relevance feedback. In general Ranking, his work in Ranking SVM is often linked to Function linking many areas of study.
The scientist’s investigation covers issues in Artificial intelligence, Data science, Knowledge management, Information retrieval and Product. His work deals with themes such as Pattern recognition and Natural language processing, which intersect with Artificial intelligence. His Pattern recognition research includes elements of Ranking and Sketch.
His Analytics study in the realm of Data science interacts with subjects such as Kernel theory. His research integrates issues of Information quality and Social media analytics in his study of Analytics. His Information retrieval study integrates concerns from other disciplines, such as Text mining, Quality and Web mining.
Weiguo Fan mostly deals with Artificial intelligence, Data science, Image, Analytics and Sketch. Artificial intelligence and Machine learning are commonly linked in his work. The Data science study combines topics in areas such as New product development, Product reviews, Purchasing and Mobile apps.
His Image research is multidisciplinary, incorporating perspectives in Visualization and Sample. Weiguo Fan interconnects Quality, Key and Product in the investigation of issues within Analytics. His Sketch study combines topics from a wide range of disciplines, such as Ranking, Object, Information retrieval and Image retrieval.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
The power of social media analytics
Weiguo Fan;Michael D. Gordon.
Communications of The ACM (2014)
Tapping the power of text mining
Weiguo Fan;Linda Wallace;Stephanie Rich;Zhongju Zhang.
Communications of The ACM (2006)
Social presence, trust, and social commerce purchase intention
Baozhou Lu;Weiguo Fan;Mi Zhou.
Computers in Human Behavior (2016)
A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism
Zheng Xiang;Qianzhou Du;Yufeng Ma;Weiguo Fan.
Tourism Management (2017)
Determinants of users’ continuance of social networking sites: A self-regulation perspective
Hui Lin;Weiguo Fan;Patrick Y.K. Chau.
A new image classification method using CNN transfer learning and web data augmentation
Dongmei Han;Qigang Liu;Weiguo Fan.
Expert Systems With Applications (2018)
Optimizing web search using web click-through data
Gui-Rong Xue;Hua-Jun Zeng;Zheng Chen;Yong Yu.
conference on information and knowledge management (2004)
Probabilistic question answering on the web
Dragomir R. Radev;Weiguo Fan;Hong Qi;Harris Wu.
the web conference (2002)
Improving web search results using affinity graph
Benyu Zhang;Hua Li;Yi Liu;Lei Ji.
international acm sigir conference on research and development in information retrieval (2005)
Understanding the determinants of online review helpfulness: A meta-analytic investigation
Hong Hong;Di Xu;G. Alan Wang;Weiguo Fan.
decision support systems (2017)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: