Active user participations and interactive communications among users in the Web 2.0 era have made it possible to elicit a vast amount of user activity information from the Web resources. At the same time, they call for a more advanced technology that enables a correct understanding of individual and/or group activities, situations, and intents of the users in various domains. There is no doubt that the vast amount of information on human experiences involving activities is going to help understanding human activities of various sorts. Our research centers around the question of how to turn the vast amount of activity-related knowledge into a form that can be utilized for various intelligence-enabled applications. Focusing on human activity knowledge, we propose a new approach to knowledge base construction by exploring and integrating structured, semi-structured and unstructured forms of activity knowledge. More specifically, we start with a manually constructed knowledge base consisting of a small number of commonsense activity frames and augment them automatically with how-to articles containing step-by-step instructions and blog posts in a free text form. To assess the utility of the proposed method and its outcome, we examined accuracy and coverage of the automatically constructed activity knowledge. We also demonstrate the utility of the constructed knowledge base in activity identification from open text. The evaluation results show that the use of the activity knowledge base indeed help improving the performance of the baseline methods for the tasks. In addition, we illustrate other potential applications of the enriched activity knowledge in different domains, such as situation-aware service recommendation and semantic web service composition.