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Creating Bengali Freebase Using Wikidata
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作者 Rukaiya Habib Mahmuda Ferdous md musfique anwar 《Journal of Computer and Communications》 2023年第5期151-160,共10页
Freebase is a large collaborative knowledge base and database of general, structured information for public use. Its structured data had been harvested from many sources, including individual, user-submitted wiki cont... Freebase is a large collaborative knowledge base and database of general, structured information for public use. Its structured data had been harvested from many sources, including individual, user-submitted wiki contributions. Its aim is to create a global resource so that people (and machines) can access common information more effectively which is mostly available in English. In this research work, we have tried to build the technique of creating the Freebase for Bengali language. Today the number of Bengali articles on the internet is growing day by day. So it has become a necessary to have a structured data store in Bengali. It consists of different types of concepts (topics) and relationships between those topics. These include different types of areas like popular culture (e.g. films, music, books, sports, television), location information (restaurants, geolocations, businesses), scholarly information (linguistics, biology, astronomy), birth place of (poets, politicians, actor, actress) and general knowledge (Wikipedia). It will be much more helpful for relation extraction or any kind of Natural Language Processing (NLP) works on Bengali language. In this work, we identified the technique of creating the Bengali Freebase and made a collection of Bengali data. We applied SPARQL query language to extract information from natural language (Bengali) documents such as Wikidata which is typically in RDF (Resource Description Format) triple format. 展开更多
关键词 KNOWLEDGE-BASE Structured Data NLP RDF
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Framework Development Using Data Mining Techniques to Predict Mortality Risk during Pandemic
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作者 Debjany Chakraborty md musfique anwar 《Journal of Computer and Communications》 2022年第8期18-25,共8页
The corona virus, which causes the respiratory infection Covid-19, was first detected in late 2019. It then spread quickly across the globe in the first months of 2020, reaching more than 15 million confirmed cases by... The corona virus, which causes the respiratory infection Covid-19, was first detected in late 2019. It then spread quickly across the globe in the first months of 2020, reaching more than 15 million confirmed cases by the second half of July. This global impact of the novel coronavirus (COVID-19) requires accurate forecasting about the spread of confirmed cases as well as continuation of analysis of the number of deaths and recoveries. Forecasting requires a huge amount of data. At the same time, forecasts are highly influenced by the reliability of the data, vested interests, and what variables are being predicted. Again, human behavior plays an important role in efficiently controling the spread of novel coronavirus. This paper introduces a sustainable approach for predicting the mortality risk during the pandemic to help medical decision making and raise public health awareness. This paper describes the range of symptoms for corona virus suffered patients and the ways of predicting patient mortality rate based on their symptoms. 展开更多
关键词 Sequential forward Feature Selection Symptom Categorization Decision Tree Attribute Selection Measure
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