Apollo is a new assured information distillation tool for uncovering likely facts in noisy social (human-centric) sensing data.
Social sensing, where users proactively document and share their observations, has received significant attention in recent years as a paradigm for crowd-sourcing observation tasks. However, it poses interesting challenges in assessing confidence in the information received.
By developing new fact-finding engines based on graph and estimation theory and leavaraging clustering tools from data mining literature, we show how to group data into sets (or claims), corroborating specific events or observations, then iteratively assess both claim and source credibility, ultimately leading to a ranking of described claims by their likelihood of occurrence. Apollo belongs to a category of tools called fact-finders. It is the first fact-finder designed and implemented specically for social sensing.
This is a collaborative work of