Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

Searching for people online is a common search task that most of us have performed at some point or other. The demonstrator also comprises a cyber-safety tool, which aims to provide education and raise awareness of the potential risks of cumulative revelations.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

• 1 With so much information about people available online it is often amazing what one can find out about someone else -- especially when information taken from different sources is pieced together to create a more detailed picture of the individual, and then used to make inferences about them (leading to cumulative revelations ).
• 2 As such, the relevance of one piece of information is often conditional and dependent on other pieces of information found.
• 3 This creates interesting and novel challenges in evaluating informationrelevance when searching personal profiles, posts and related information about an individual, as well as the potential risks that can arise from such revelations.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source: