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Mining Stack Overflow for API class recommendation using DOC2VEC and LDA
Published 2021-10-01“…Abstract To address the lexical gaps between natural language (NL) queries and Application Programming Interface (API) documentations, and between NL queries and programme code, this study developed a novel approach for recommending Java API classes that are relevant to the programming tasks described in NL queries. A Doc2Vec model was trained using question titles mined from Stack Overflow. …”
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A real time approach to user interest classification using DPI
Published 2016-12-01Subjects: Get full text
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An Empirical Configuration Study of a Common Document Clustering Pipeline
Published 2023-09-01“…In this paper, we study document clustering with the common clustering pipeline that includes vectorization with BERT or Doc2Vec, dimension reduction with PCA or UMAP, and clustering with K-Means or HDBSCAN. …”
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Human-interpretable clustering of short text using large language models
Published 2025-01-01“…The resulting clusters are found to be more distinctive and more human-interpretable than clusters produced using the popular methods of doc2vec and latent Dirichlet allocation. The success of the clustering approach is quantified using human reviewers and through the use of a generative LLM. …”
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Graph Convolutional Network for Word Sense Disambiguation
Published 2021-01-01“…Discriminative features and sentence containing the ambiguous word are used as nodes to construct the WSD graph. Word2Vec tool, Doc2Vec tool, pointwise mutual information (PMI), and TF-IDF are applied to compute embeddings of nodes and edge weights. …”
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A Novel Method for News Recommendation on Websites Using the Clustered-Vectors Optimization Algorithm
Published 2025-01-01“…Experimental results indicated that the proposed CVO algorithm outperformed five well-known algorithms, which were TF-IDF, Word2Vec, Doc2Vec, Bag-of-Words (BoW), and Transformer, in terms of predictive performance. …”
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Zero-BertXGB: An Empirical Technique for Abstract Classification in Systematic Reviews
Published 2025-01-01“…Addressing this gap, this study employs GloVe for word embedding via matrix factorization, FastText for character n-gram representation, and Doc2Vec for capturing paragraph-level semantics. A novel Zero-BertXGB technique is introduced, integrating a transformer-based language model, zero-shot learning, and an ML classifier to enhance abstract screening and classification into “Include” or “Exclude” categories. …”
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