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- W3166633100 abstract "In a world where technology has grown to be a mega thing impacting the lives of mankind to a greater extent, a common man is still having huge difficulty in adapting the available technical solutions immediately. There are so many basic tasks that are performed in the day-to-day lives of people which take a lot of effort and time and can be automated with the help of technology but still, and humans are more prone to do them manually. One such example is taking subjective examinations by students and then evaluation of the answer sheets manually by the teachers. So, to ease the process of subjective answer checking, a web application has been developed that can check the subjective answers written by the students with the same efficiency as in the case of manual checking by the teachers. Using this software, teachers can set the question paper and students can take their examination by getting their answers checked simultaneously. The model’s development is settled with the Word2Vec skip-gram model, Natural Language ToolKit (NLTK) modules, and Flask Python framework, whereas all the data have been stored in the form of relational database tables which are inserted and fetched through the SQL queries. The Word2Vec skip-gram model is used to make the vocabulary of terms and to find their corresponding word embeddings (feature vectors). The paper proposes the development of a model that will make a time-consuming and tiresome task like manual answer checking as effortless as possible." @default.
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- W3166633100 date "2021-01-01" @default.
- W3166633100 modified "2023-10-16" @default.
- W3166633100 title "Design of Automatic Answer Checker" @default.
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- W3166633100 doi "https://doi.org/10.1007/978-981-33-6984-9_20" @default.
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