Essays about: "neural information retrieval"

Showing result 1 - 5 of 21 essays containing the words neural information retrieval.

  1. 1. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Laura Galera Alfaro; [2023]
    Keywords : Explainable Artificial Intelligence; Learning To Rank; Local ModelAgnostic Interpretability; Ranking Generalized Additive Models;

    Abstract : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. READ MORE

  3. 2. The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM

    University essay from KTH/Matematik (Inst.)

    Author : Oscar Blommegård; [2023]
    Keywords : The Impact of the Retrieval Text Set for Text Sentiment Classification With the Retrieval-Augmented Language Model REALM; Hämtningsförstärkta språkmodeller; Natural Language Processing; Transformers; Djupinlärning; Textklassificering;

    Abstract : Large Language Models (LLMs) have demonstrated impressive results across various language technology tasks. By training on large corpora of diverse text collections from the internet, these models learn to process text effectively, allowing them to acquire comprehensive world knowledge. READ MORE

  4. 3. Violin Artist Identification by Analyzing Raga-vistaram Audio

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Nandakishor Ramlal; [2023]
    Keywords : Artist identification; Music information retrieval; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Embeddings; log-Melspectrogram; Artistidentifiering; återhämtning av musikinformation; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Inbäddningar; log-Melspektrogram;

    Abstract : With the inception of music streaming and media content delivery platforms, there has been a tremendous increase in the music available on the internet and the metadata associated with it. In this study, we address the problem of violin artist identification, which tries to classify the performing artist based on the learned features. READ MORE

  5. 4. Re-ranking search results with KB-BERT

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Bjarki Viðar Kristjánsson; [2022]
    Keywords : Natural language processing; Information retrieval; BERT; KB-BERT; Search evaluation; Naturlig språkbehandling; Informationssökning; BERT; KB-BERT; Sökutvärdering;

    Abstract : This master thesis aims to determine if a Swedish BERT model can improve a BM25 search by re-ranking the top search results. We compared a standard BM25 search algorithm with a more complex algorithm composed of a BM25 search followed by re-ranking the top 10 results by a BERT model. READ MORE

  6. 5. Duplicate detection of multimodal and domain-specific trouble reports when having few samples : An evaluation of models using natural language processing, machine learning, and Siamese networks pre-trained on automatically labeled data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Viktor Karlstrand; [2022]
    Keywords : Duplicate detection; Bug reports; Trouble reports; Natural language processing; Information retrieval; Machine learning; Siamese neural network; Transformers; Automated data labeling; Shapley values; Dubblettdetektering; Felrapporter; Buggrapporter; Naturlig språkbehandling; Informationssökning; Maskininlärning; Siamesiska neurala nätverk; Transformatorer; Automatiserad datamärkning; Shapley-värden;

    Abstract : Trouble and bug reports are essential in software maintenance and for identifying faults—a challenging and time-consuming task. In cases when the fault and reports are similar or identical to previous and already resolved ones, the effort can be reduced significantly making the prospect of automatically detecting duplicates very compelling. READ MORE