This paper presents techniques of retrieving useful information from a mixture of Web pages collected from either question-answer sites (Q&amp
A sites) or Web search engines. The proposed techniques are designed to discover the maximum possible amount of know-how knowledge from such collections of Web pages, where know-how knowledge is defined as text contents qualified as information source regarding specific domain of questions. The major intent is to build a framework that selects helpful information to provide answers to various problems of interest, such as useful tips to a question. Techniques in this paper primarily attempt to complement knowledge available on Q&amp
A sites with pages collected from search engines via topic models. In order to argue that pages collected from search engine are truly supplements to know-how knowledge on Q&amp
A sites we verify how much extra useful information the Web search engine is able to provide by manually inspecting Web pages aggregated by the topic model.