Search (5 results, page 1 of 1)

  • × author_ss:"Liu, J."
  1. Liu, J.; Zhou, Z.; Gao, M.; Tang, J.; Fan, W.: Aspect sentiment mining of short bullet screen comments from online TV series (2023) 0.01 
    0.010818963 = product of:
  0.04327585 = sum of:
    0.04327585 = weight(_text_:reference in 1018) [ClassicSimilarity], result of:
      0.04327585 = score(doc=1018,freq=2.0), product of:
        0.19255297 = queryWeight, product of:
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.047329273 = queryNorm
        0.22474778 = fieldWeight in 1018, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.0683694 = idf(docFreq=2055, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1018)
  0.25 = coord(1/4)
    Abstract
    Bullet screen comments (BSCs) are user-generated short comments that appear as real-time overlays on many video platforms, expressing the audience opinions and emotions about different aspects of the ongoing video. Unlike traditional long comments after a show, BSCs are often incomplete, ambiguous in context, and correlated over time. Current studies in sentiment analysis of BSCs rarely address these challenges, motivating us to develop an aspect-level sentiment analysis framework. Our framework, BSCNET, is a pre-trained language encoder-based deep neural classifier designed to enhance semantic understanding. A novel neighbor context construction method is proposed to uncover latent contextual correlation among BSCs over time, and we also incorporate semi-supervised learning to reduce labeling costs. The framework increases F1 (Macro) and accuracy by up to 10% and 10.2%, respectively. Additionally, we have developed two novel downstream tasks. The first is noisy BSCs identification, which reached F1 (Macro) and accuracy of 90.1% and 98.3%, respectively, through fine-tuning the BSCNET. The second is the prediction of future episode popularity, where the MAPE is reduced by 11%-19.0% when incorporating sentiment features. Overall, this study provides a methodology reference for aspect-level sentiment analysis of BSCs and highlights its potential for viewing experience or forthcoming content optimization.
  2. Liu, J.: CIP in China : the development and status quo (1996) 0.00 
    0.004809347 = product of:
  0.019237388 = sum of:
    0.019237388 = product of:
      0.038474776 = sum of:
        0.038474776 = weight(_text_:22 in 5528) [ClassicSimilarity], result of:
          0.038474776 = score(doc=5528,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.23214069 = fieldWeight in 5528, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=5528)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Source
    Cataloging and classification quarterly. 22(1996) no.1, S.69-76
  3. Zhou, D.; Lawless, S.; Wu, X.; Zhao, W.; Liu, J.: ¬A study of user profile representation for personalized cross-language information retrieval (2016) 0.00 
    0.0040077893 = product of:
  0.016031157 = sum of:
    0.016031157 = product of:
      0.032062314 = sum of:
        0.032062314 = weight(_text_:22 in 3167) [ClassicSimilarity], result of:
          0.032062314 = score(doc=3167,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.19345059 = fieldWeight in 3167, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3167)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    20. 1.2015 18:30:22
  4. Zhang, Y.; Liu, J.; Song, S.: ¬The design and evaluation of a nudge-based interface to facilitate consumers' evaluation of online health information credibility (2023) 0.00 
    0.0040077893 = product of:
  0.016031157 = sum of:
    0.016031157 = product of:
      0.032062314 = sum of:
        0.032062314 = weight(_text_:22 in 993) [ClassicSimilarity], result of:
          0.032062314 = score(doc=993,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.19345059 = fieldWeight in 993, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=993)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    22. 6.2023 18:18:34
  5. Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023) 0.00 
    0.0040077893 = product of:
  0.016031157 = sum of:
    0.016031157 = product of:
      0.032062314 = sum of:
        0.032062314 = weight(_text_:22 in 1012) [ClassicSimilarity], result of:
          0.032062314 = score(doc=1012,freq=2.0), product of:
            0.16573904 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047329273 = queryNorm
            0.19345059 = fieldWeight in 1012, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1012)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    22. 6.2023 14:55:20

Authors

Years

Themes