Art Experiments and Cultural Preservation during a Pandemic: A Case Study Lembah Gana Festival in 2020

This study aims to reveal artistic expressions and forms of cultural preservation at the Lembah Gana Festival in Semarang Regency. This research is interesting to do because no research has been found on the Lembah Gana Festival. The urgency of this research lies in the introduction of cultural heritage, especially ancient Java. The problem is that most people forget about historical remains, both physically (tangible) and non-physically (intagible). The object and location of this research is the Lembah Gana Festival in Semarang Regency. This research is in the realm of ethnographic research. The research method used is document extraction, observation, and in-depth interviews to related parties. The research data were analyzed descriptively qualitatively. The novelty of the findings lies in the ability of the Lembah Gana Festival to bring back ancient Javanese culture. In addition, the research results show that the Lembah Gana Festival is increasingly existing and efforts to preserve culture have received enthusiasm from the people of Semarang Regency during the pandemic. The Festival Model which is conducted online, makes it easier for the audience to access.

A Deep Cascade Model for Multi-Document Reading Comprehension

A fundamental trade-off between effectiveness and efficiency needs to be balanced when designing an online question answering system. Effectiveness comes from sophisticated functions such as extractive machine reading comprehension (MRC), while efficiency is obtained from improvements in preliminary retrieval components such as candidate document selection and paragraph ranking. Given the complexity of the real-world multi-document MRC scenario, it is difficult to jointly optimize both in an end-to-end system. To address this problem, we develop a novel deep cascade learning model, which progressively evolves from the documentlevel and paragraph-level ranking of candidate texts to more precise answer extraction with machine reading comprehension. Specifically, irrelevant documents and paragraphs are first filtered out with simple functions for efficiency consideration. Then we jointly train three modules on the remaining texts for better tracking the answer: the document extraction, the paragraph extraction and the answer extraction. Experiment results show that the proposed method outperforms the previous state-of-the-art methods on two large-scale multidocument benchmark datasets, i.e., TriviaQA and DuReader. In addition, our online system can stably serve typical scenarios with millions of daily requests in less than 50ms.

Keywords extraction in Chinese–Vietnamese bilingual news based on hypergraph

The keywords extraction of bilingual news events in China and Vietnam has a very important role in understanding bilingual news events. It can quickly locate and briefly compare the news of the same events reported by the two countries. Chinese–Vietnam news texts are typically unstructured big data. How to extract the keywords that characterize the news in these unstructured data is the difficult problem of unstructured big data analysis. Bilingual documents are difficult to understand because bilingual Chinese and Vietnamese are not in the same language space. However, the hypergraph of the hypergraph model can better express the multiple relations of the vocabulary association and the entity association for bilingual news. Therefore, a method based on hypergraph for bilingual news keywords extraction is proposed. In this method, bilingual news words are extracted to construct a bilingual word set, and the words are taken as vertices. Chinese–Vietnamese sentences and bilingual words with the same semantic meaning as different types of hyperedges and the bilingual word frequency are used as the attribute to construct a bilingual news item word hypergraph model. Then, the directional diffusion algorithm in the wireless sensor network is used to iteratively calculate the weights of the vertices so as to realize the extraction of keywords in the Chinese–Vietnam bilingual news. The experimental results show that the proposed hypergraph method is better than the single-document extraction method, which can better obtain the keywords of the bilingual unstructured text data.