Finding jokes online is like trawling through heaps of irregular websites and sources. At times the jokes are not even all that funny. There are also a whole range of joke topics available and constantly growing as appetites and tastes for humor changes over time. Jokes are also an art form often deeply rooted in unique styles and personal wit that is characteristic in the manner with which it is told. However, on the web, reading interesting jokes is still a very much seeped in unchartered waters of unearthing the right joke for the right context - a very much problematic exercise. Here in lies knowledge discovery from exploring the deep web as a graph and contextually for sources of jokes embedded within web documents and extracting the many facades in semantics. Semantic web for jokes is a right form to apply here as well as a unique ontology to go with it. Moreover, a linked data for exploring the entire web as well as connecting the many joke sites and numerous sources for aggregation. People desire humor in their lives and is often the cure for many ills. Furthermore, the application of such semantically aggregated exploration could then be used for building useful search sites but also to provide smart natural language aware bots that could provide for a witty personable experience to a user both via the desktop browser as well as on mobile. Once a structure in contextual knowledge discovery is in place, there are insurmountable uses that could be applied providing the answer to the web in form of extensibility and reuse.
