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At its core, this project is about memory, the relationship between memory and official histories, and the role that the performing arts have in constructing our cultural memories. Through multi-sited fieldwork in Vietnam (Hanoi, Tam Kỳ, Quy Nhơn, and Hồ Chí Minh City) and the Vietnamese refugee community of southern California, my research focuses on the musical theatre genre hát bội, with origins that can be traced as far back as the eleventh century. This art form has undergone transformations during Vietnam's tumultuous history, through French colonialism, independence, a communist revolution, recent economic reforms, and in the refugee community that fled the war. The myriad ways (films, fiction, memoirs, photographs, political speeches, memorials) in which Vietnamese history, especially the war, has been told, are often highly contested. This dissertation centers around the social and political meanings ascribed to hát bội today across national and diasporic communities, and how hát bội is a medium through which the negotiation and construction of contested memories have taken place. In Vietnam, I examine three state-sponsored hát bội troupes and their performances at a highly political national competition, organized by the government. In this state-sponsored competition, I look at the ways in which performances of hát bội have been able to both sustain and subvert nationalist memories. In southern California, I argue that performances of hát bội are framed in the context of nostalgia, loss, and longing for a no longer existing homeland, and in the context of American society that has so often left South Vietnamese experiences unacknowledged. Through the art from of hát bội, I examine lasting effects of colonialism and imperialism in Vietnam's history and in the Vietnamese refugee community, and how this story has been told.

Text representation models are very important pre-processing step in various domains such as text mining, information retrieval, natural language processing. In this paper we summarize graph-based text representation models. Graph-based model can capture structural information such as the location, order and proximity of term occurrence, which is discarded under the standard text vector representation models. We have tested this graph model in Vietnamese text classification system.