The Knowledge Map Analysis of User Profile Research Based on CiteSpace
With the development of big data technology, user profile, as an effective method for delineating user characteristics, has attracted extensive attention from researchers and practitioners. Rich related literatures have been accumulated. How to find the key factors and the new direction from such a big library is a difficult problem for a new researcher entering the field. The knowledge map can be used to visualize the development trend, the frontier field and the overall knowledge structure from these researches. Therefore, we choose web of science database as the literature search engine and use CiteSpace to construct the user profile knowledge map. Through these maps, we analyze the important authors and countries, make the common word analysis and co-citation analysis, study the hot spots and important literatures. The time distribution shows that some foundational theories in user profile were produced at the second stage from 2004 to 2013. What’s more, from the geographical distribution, we find that user profile, as an abstract concept, has no unified framework. Each country focuses on the different research points. From the knowledge map of keywords, we find that the top three algorithmic techniques used in constructing user profile are clustering, classification, and collaborative filtering. At the same time, user profile is also used in some specific applications, such as anomaly detection, behavior analysis, and information retrieval.
KeywordsUser profile CiteSpace Knowledge map Visualization Big data
This work was supported by Science and Technology Program of Guangzhou, China (No. 201707010495), Foundation for Distinguished Young Talents in Higher Education of Guangzhou, China (No. 2013LYM0032), Project supported by Guangdong Province Universities, China (No. 2015KTSCX046), and Foundation for Technology Innovation in Higher Education of Guangdong Province, China (No. 2013KJCX0085).
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