The rapid growth of e-commerce has made product recommendation systems essential for enhancing customer experience and driving business success. This research proposes an advanced recommendation framework that integrates sentiment analysis (SA) and collaborative filtering (CF) to improve recommendation accuracy and user satisfaction. The methodology involves feature-level sentiment analysis with a multi-step pipeline: data preprocessing, feature extraction using a log-term frequency-based modified inverse class frequency (LFMI) algorithm, and sentiment classification using a Multi-Layer Attention-based Encoder-Decoder Temporal Convolution Neural Network (MLA-EDTCNet).
View Article and Find Full Text PDFBackground: Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of malignant plasma cells within the bone marrow. The disease's complexity is underpinned by a variety of genetic and molecular abnormalities that drive its progression.
Methods: This review was conducted through a state-of-The-art literature search, primarily utilizing PubMed to gather peer-reviewed articles.
Hyperglycemia, a key characteristic of type 2 diabetes mellitus (T2DM), highlights the need for effective management strategies. This study aims to analyze the impact of multistrain probiotic supplementation on glycemic control in T2DM patients. During a 24-week randomized controlled trial involving 130 participants, subjects were assigned to either a probiotic group or a placebo group.
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