Essays about: "Avsiktsklassificering"
Found 5 essays containing the word Avsiktsklassificering.
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1. Recommendation of Text Properties for Short Texts with the Use of Machine Learning : A Comparative Study of State-of-the-Art Techniques Including BERT and GPT-2
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Text mining has gained considerable attention due to the extensive usage ofelectronic documents. The significant increase in electronic document usagehas created a necessity to process and analyze them effectively. READ MORE
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2. QPLaBSE: Quantized and Pruned Language-Agnostic BERT Sentence Embedding Model : Production-ready compression for multilingual transformers
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Transformer models perform well on Natural Language Processing and Natural Language Understanding tasks. Training and fine-tuning of these models consume a large amount of data and computing resources. Fast inference also requires high-end hardware for user-facing products. READ MORE
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3. 'Sorry, I didn't understand that' : A comparison of methods for intent classification for social robotics applications
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : An important feature in a social robot is the ability to understand natural language. One of the core components in a typical system for natural language understanding (NLU) is so called intent classification; the action of classifying user utterances based on the underlying intents of the user. READ MORE
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4. Intent classification through conversational interfaces : Classification within a small domain
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Natural language processing and Machine learning are subjects undergoing intense study nowadays. These fields are continually spreading, and are more interrelated than ever before. A case in point is text classification which is an instance of Machine learning(ML) application in Natural Language processing(NLP). READ MORE
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5. The Effect of Data Quantity on Dialog System Input Classification Models
University essay from KTH/Hälsoinformatik och logistikAbstract : This paper researches how different amounts of data affect different word vector models for classification of dialog system user input. A hypothesis is tested that there is a data threshold for dense vector models to reach the state-of-the-art performance that have been shown with recent research, and that character-level n-gram word-vector classifiers are especially suited for Swedish classifiers–because of compounding and the character-level n-gram model ability to vectorize out-of-vocabulary words. READ MORE
