A Survey of User Profiling: State-of-the-Art, Challenges, and Solutions

Abstract

Advancements in information and communication technology, and online web users have given attention to the virtual representation of each user, which is crucial for effective service personalization. Meeting users need and preferences is an ongoing challenge in service personalization. This issue can be addressed through the building of a comprehensive user profile. A user profile is the summary of the user's interests, characteristics, behaviours, and preferences, while user profiling is the system of collecting, organizing and inferring the user profile information. Many reviews on user profiling have been conducted but none focused on the effective profile modeling process. Hence, this article aims to provide a review of the recent state-of-the-art approach to user profiling. These include methods, description, characteristics, and taxonomy of the user profile. The study of the existing user profiling modeling in the aspect of data acquisition, feature extraction, profiling techniques, and profiling approaches (with the identification of their strengths and weaknesses) and the performance measures are also provided. In addition, the research challenges were also discussed with a focus on privacy, datasets, cold start issues, trust issues, and computational complexity. Moreover, the article identified an open research direction that serves as solutions to the identified challenges and motivation for further researchers in advancing user profiling. The findings showed that an effective modeling process enhances the construction of accurate user profile for service personalization.

Data quality assessment in digital score libraries

“…Implementing personalization. In practice, the fitness for use inherent feature of data quality implies that a DSL has to offer a personalization of the data quality information, for instance, by taking users' profiles [11] into account (a general definition of a profile in the context of DSL is proposed in [6]). In terms of implementation, the DSL allows the user to interact with its system via graphical user interface tools (GUI), to let her/him define her/his profile.…”

User Behavior Analysis by Cross-Domain Log Data Fusion

“…User behavior data fusion in this paper refers to identifying multiple representations of an individual user or a group of users, and mapping source data into target representation [4]. A user behavior model or profile is constructed to describe user characteristics by extracting diverse information interests and accumulated behavior preferences.…”

Engineering Reliable Interactions in the Reality-Artificiality Continuum

“…We disregard the profiling issue, already well covered by the literature [16,50], and we discuss how reliability of interaction could be addressed by exploiting ontologies and runtime verification.…”