This article has examined how the Hallyu phenomenon is integrated into a transnational global cultural landscape, focusing on Chilean reception of K-pop. It analyzed how Hallyu fans engage with a social media-saturated environment in Chile, mapping out transnational pop cultural flows within the digital media environment through which the participatory culture of media users is spread. What is interesting is that Chilean society, in general, shows negative attitudes toward K-pop fans. More importantly, while many Chileans consider K-pop fans weird and strange, often disparaging their family members and friends for liking such music, the marginalization of K-pop fans in Chile promotes a greater sense of bonding among them through the affinity spaces of social media. Under this circumstance, most of our interviewees explained that digital media plays a vital role in the dissemination of K-pop in Chile and Latin America. Unlike Hallyu fans in other regions, K-pop fans in Chile have developed cultural intimacy specific to digital site-media, primarily in the realm of social media, and K-pop generates the creation of affinity spaces via different social media platforms.
To discriminate among all possible diagnoses using Hou's theory of measurement in diagnosis from first principles, one has to derive all minimal conflict sets from a known conflict set. However, the result derived from Hou's method depends on the order of node generation in CS-trees. We develop a derivation method with mark set to overcome this drawback of Hou's method. We also show that our method is more efficient in the sense that no redundant tests have to be done. An enhancement to our method with the aid of extra information is presented. Finally, a discussion on top-down and bottom-up derivations is given.
Understanding temporal expressions in natural language is a key step towards incorporating temporal information in many applications. In this paper we describe a system capable of anchoring such expressions in English: system TEA features a constraint-based calendar model and a compact representational language to capture the intensional meaning of temporal expressions. We also report favorable results from experiments conducted on several email datasets.
Automatic extraction and reasoning over temporal properties in natural language discourse has not had wide use in practical systems due to its demand for a rich and compositional, yet inference-friendly, representation of time. Motivated by our study of temporal expressions from the Penn Treebank corpora, we address the problem by proposing a two-level constraint-based framework for processing and reasoning over temporal information in natural language. Within this framework, temporal expressions are viewed as partial assignments to the variables of an underlying calendar constraint system, and multiple expressions together describe a temporal constraint-satisfaction problem (TCSP). To support this framework, we designed a typed formal language for encoding natural language expressions. The language can cope with phenomena such as under-specification and granularity change. The constraint problems can be solved using various constraint propagation and search methods, and the solutions can then be used to answer a wide range of time-related queries.
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