Browsing by Subject "Natural Language Processing"

Now showing items 1-6 of 6

    • Characterization of NON-ISA factual sentences in english 

      Kansagara, Vishal J. (Dhirubhai Ambani Institute of Information and Communication Technology, 2014)
      Availability to reason for extraction of knowledge has made Ontology Learning subject of intensive study for past couple of years. With the scaling of the domain, time taken to manually conceptualize the domain knowledge ...

    • Crime information extraction from news articles 

      Gohel, Prashant (Dhirubhai Ambani Institute of Information and Communication Technology, 2018)
      In the modern era all news reportings are available in digital form. Most newsagencies put it on their website and are freely available. This motivates us totry extracting some information from online news reporting. While ...

    • Distant supervision for relation extraction 

      Doshi, Prarthana (Dhirubhai Ambani Institute of Information and Communication Technology, 2018)
      Relation Extraction(RE) is one of important task of Information Extraction. InformationExtraction is used to get data from natural language text. Relation extractionis done using different methods. Most techniques found ...

    • Improving the Quality of Data to be used for Text Classification task 

      Mehta, Stuti (Dhirubhai Ambani Institute of Information and Communication Technology, 2021)
      Text Classification is one of the most basic tasks of Natural Language Processing (NLP) and efforts have been made to improve the performance of the task by making changes to the classifier model. For any NLP problem, the ...

    • Sentence detection 

      Shah, Pushya (2020)
      Sentence detection is a very important task for any natural language processing (NLP) application. Accuracy and performance of all other downstream natural language processing (NLP) task like Sentiment, Text Classification, ...

    • What does BERT learn about questions 

      Tyagi, Akansha (2020)
      Recent research in Question Answering is highly motivated by the introduction of the BERT [5] model. This model has gained considerable attention since the researcher of Google AI Language has claimed state-of-the-art ...