This study addresses the extraction of advice-revealing sentences from web forums, focusing on its utility in the travel domain. Instead of treating the problem as simple classification, the study defines it as a sequence labeling issue and uses various features, including syntactic, context, and sentence informativeness features. A Hidden Markov Model (HMM) is employed for labeling sequential sentences, showing superior performance in the task. This research represents the first attempt to systematically extract advice-revealing sentences from web forums.