A scientometric review of emerging trends and new developments in recommendation systems

Recommendation systems have drawn an increasingly broad range of interest since early 1990s. Recently, a search with the query of "recommendation systems" on Google Scholar found over 32,000 documents. As the volume of the literature grows rapidly, thus, a systematic review of the diverse research field and its current challenges becomes essential. This study surveys the literature of recommendation systems between 1992 and 2014. The overall structure of its intellectual landscape is illustrated in terms of thematic concentrations of co-cited references and emerging trends of bursting keywords and citations to references. Our review is based on two sets of bibliographic records retrieved from the Web of Science. The core dataset, obtained through a topic search, contains 2573 original research and review articles. The expanded dataset, consisting of 12,916 articles and reviews, was collected by citation expansion. We identified intellectual landscapes, landmark articles and bursting keywords of the domain in core and broader perspectives. We found that a number of landmark studies in 1980s and 1990s and techniques such as LDA, pLSI, and matrix factorization have tremendously influenced the development of the recommendation systems research. Furthermore, our study reveals that the field of recommendation systems is still evolving and developing. Thematic trends in recommendation systems research reflect the development of a wide variety of information systems such as the World Wide Web and social media. Finally, collaborative filtering has been a dominant research concept of the field. Recent emerging topics focus on enhancing the effectiveness of recommendation systems by addressing diverse challenges.