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Extracting Keywords from Multi-party Live Chats

Live chats have become a popular form of communication, connecting people all over the globe. We believe that one of the simplest approaches for providing topic information to users joining a chat is keywords. In this paper, we present a method to automatically extract contextually relevant keywords for multi-party live chats. In our work, we identify keywords that are associated with specific dialogue acts as well as the occurrences of keywords across the entire conversation. In this way, we are able to identify distinguishing features of the chat based on structural information derived from live chats and predicted dialogue acts. In evaluation, we find that using structural information and predicted dialogue acts performs well, and that conventional methods do not work well over live chats.

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