Mining user-intents has been a core platform in semantic web search and intelligent test mining. Prior art on these arena lacks infeasibility in materialization of theoretical foundations on factual viewpoints. Literatures and artifacts are needed to twitch conceptualization of formalism and methodologies on distinct domains under user-intent mining. This chapter provides a basis formulation of automata, theories and algorithm design approach for user-intent mining on social networks. The aim and the scope of this chapter is introspection of user’s aspiration in online search mechanics symbolizing business intelligence. A concrete approach to retrieve named entities from live social networks has been modelled in this chapter. The source for retrieval are public logs, blog, social channels and web-o-media has been constructed as an activity model which is modelled as transient in nature. Formulation of automata to recognize intent-keywords and the algorithm to reason the context of dialogue on live –talks have been described. This chapter describes principles and mathematical approach to design ontologies for intelligent mining for reasoning in live-talks overcoming the problem of out-of-vocabulary (OOV).

opinion mining, social networks, ontology, live-talk reasoning, out-of-vocabulary (OOV)

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