HealthAid: Extracting domain targeted high precision procedural knowledge from on-line communities

Abstract

Recent advances in semantic web have shown how entity related searches have benefited from entity-based knowledge graphs. However, much of the commonsense knowledge about the real world is in the form of procedures or sequences of actions. Also, search log analysis shows that ‘how-to queries’ make up a significant amount of users’ queries. Unfortunately, these kinds of knowledge are missing from most knowledge graphs and commonsense knowledge bases in use. To empower semantic search, and other intelligent applications, computers need a much broader understanding of the world properties of everyday objects, human activities, and more. Luckily, such knowledge is abundantly available on-line and can be accessed from how-to communities. One domain of interest by on-line communities is the health domain, whereby users usually seek home remedies to common health-related issues. An example of such queries might be ‘how to stop nausea using acupressure’ or ‘how to aid digestion naturally’. To answer such questions, we need systems that understand natural language and knowledge bases with task frames of solutions in a holistic approach, including the tools required, the agents involved, and the temporal order of the actions. Our goal is to construct a machine-readable domain targeted high precision procedural knowledge base containing task frames. We developed a pipeline of methods leveraging open information extraction tool to extract procedural knowledge by tapping into on-line communities. Also, we devised a mechanism to canonicalize the task frames into clusters based on the similarity of the problems they intend to solve. The resulting know-how knowledge base, HealthAidKB, consists of more than 71 K task frames which are structured hierarchically and categorically; and can be used in many applications such as semantic search, digital personal assistants, human-computer dialog and computer vision. A comprehensive evaluation of our knowledge base shows high accuracy.