An Ontology-Based Technique for Online Profile Resolution

Cortis, Keith; Scerri, Simon; Rivera, Ismael; Handschuh, Siegfried

doi:10.1007/978-3-319-03260-3_25

Cited by 28 publications

(14 citation statements)

References 9 publications

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“…Apart from usernames and images, several researchers have focused on considering various profile attributes to improve the prediction performance [51,52,53,54,55,56]. A heuristic approach based on using the username, e-mail, and birth city attributes was proposed by Carmagnola et al [51].…”

Section: Feature-based Predictionmentioning

confidence: 99%

Interlayer link prediction in multiplex social networks: An iterative degree penalty algorithm

Tang

Jiang

Chen

et al. 2020

Knowledge-Based Systems

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Section: Feature-based Predictionmentioning

confidence: 99%

Interlayer link prediction in multiplex social networks: An iterative degree penalty algorithm

Tang

Jiang

Chen

et al. 2020

Knowledge-Based Systems

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“…They use 27 features grouped into three types: name based features, general user info based features and social network topological based features. In [8] a weighted ontology-based user profile resolution technique is proposed for profile matching. Generally, these techniques assume that the two user profiles under investigation intentionally share attributes and features.…”

Section: Identifying and Matching User Profiles In Snsmentioning

confidence: 99%

Profile resolution across multilayer networks through smartphone camera fingerprint

Bertini

Sharma

Iannì

et al. 2014

Proceedings of the 19th International Database Engineering &Amp; Applications Symposium on - IDEAS '15

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In the last decade, various social platforms have been introduced on the web. Due to their specific orientation (friendship, professional connections, image sharing, etc.) users often join multiple networks. An important problem across these networks is the resolution of users profiles. That is, to identify if set of user profiles from different networks with different user ids or nicknames belong to the same user. The problem is more meaningful for resolving different profiles in digital forensic and criminal investigations. In this paper, we propose a method for profile resolution with the help of pictures being posted on different social platforms. We use the smartphone cameras which have become the source of instant image capturing and uploading process. In particular, we exploit the characteristic noise present in the images due to the manufacturing defects, to match user profiles across social platforms. To test our approach we select five different smartphones with two pairs of identical models, and three social platforms, namely Facebook, Google+ and WhatsApp. We evaluate our approach using real dataset of 1000 highresolution pictures. The results indicate that even in the worst case our approach can provide profile matching upto 89.83%.

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“…Goga [10] linked accounts belonging to the same person identity, based solely on the profile information. Cortis [11] proposed a weighted ontology-based user profile resolution technique. Abel et al [12] aggregated user profiles and matched users across systems.…”

Section: Profile-based User Identificationmentioning

confidence: 99%

“…Many studies have addressed the user identification problem by examining public user profile attributes, including screen name, birthday, location, gender, profile photo, etc. [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17]. Since these attributes do not require exclusivity and are easily faked by users for different purposes (including malicious users), these schemes are quite fragile.…”

Section: Introductionmentioning

confidence: 99%

Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks

Zhou

Liang

Zhang

et al. 2016

IEEE Trans. Knowl. Data Eng.

173

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The last few years have witnessed the emergence and evolution of a vibrant research stream on a large variety of online Social Media Network (SMN) platforms. Recognizing anonymous, yet identical users among multiple SMNs is still an intractable problem. Clearly, cross-platform exploration may help solve many problems in social computing in both theory and applications. Since public profiles can be duplicated and easily impersonated by users with different purposes, most current user identification resolutions, which mainly focus on text mining of users' public profiles, are fragile. Some studies have attempted to match users based on the location and timing of user content as well as writing style. However, the locations are sparse in the majority of SMNs, and writing style is difficult to discern from the short sentences of leading SMNs such as Sina Microblog and Twitter. Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective. The real-world friend cycle is highly individual and virtually no two users share a congruent friend cycle. Therefore, it is more accurate to use a friendship structure to analyze cross-platform SMNs. Since identical users tend to set up partial similar friendship structures in different SMNs, we proposed the Friend Relationship-Based User Identification (FRUI) algorithm. FRUI calculates a match degree for all candidate User Matched Pairs (UMPs), and only UMPs with top ranks are considered as identical users. We also developed two propositions to improve the efficiency of the algorithm. Results of extensive experiments demonstrate that FRUI performs much better than current network structure-based algorithms.

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An Ontology-Based Technique for Online Profile Resolution

Cited by 28 publications

References 9 publications

Interlayer link prediction in multiplex social networks: An iterative degree penalty algorithm

Interlayer link prediction in multiplex social networks: An iterative degree penalty algorithm

Profile resolution across multilayer networks through smartphone camera fingerprint

Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks

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