Document (#42044)

Author
Agarwal, B.
Ramampiaro, H.
Langseth, H.
Ruocco, M.
Title
¬A deep network model for paraphrase detection in short text messages
Source
Information processing and management. 54(2018) no.6, S.922-937
Year
2018
Abstract
This paper is concerned with paraphrase detection, i.e., identifying sentences that are semantically identical. The ability to detect similar sentences written in natural language is crucial for several applications, such as text mining, text summarization, plagiarism detection, authorship authentication and question answering. Recognizing this importance, we study in particular how to address the challenges with detecting paraphrases in user generated short texts, such as Twitter, which often contain language irregularity and noise, and do not necessarily contain as much semantic information as longer clean texts. We propose a novel deep neural network-based approach that relies on coarse-grained sentence modelling using a convolutional neural network (CNN) and a recurrent neural network (RNN) model, combined with a specific fine-grained word-level similarity matching model. More specifically, we develop a new architecture, called DeepParaphrase, which enables to create an informative semantic representation of each sentence by (1) using CNN to extract the local region information in form of important n-grams from the sentence, and (2) applying RNN to capture the long-term dependency information. In addition, we perform a comparative study on state-of-the-art approaches within paraphrase detection. An important insight from this study is that existing paraphrase approaches perform well when applied on clean texts, but they do not necessarily deliver good performance against noisy texts, and vice versa. In contrast, our evaluation has shown that the proposed DeepParaphrase-based approach achieves good results in both types of texts, thus making it more robust and generic than the existing approaches.
Content
Vgl.: https://doi.org/10.1016/j.ipm.2018.06.005.
Theme
Computerlinguistik

Similar documents (author)

  1. Agarwal, N.K.: Exploring context in information behavior : seeker, situation, surroundings, and shared identities (2018) 6.10 
    6.0972233 = sum of:
  6.0972233 = weight(author_txt:agarwal in 992) [ClassicSimilarity], result of:
    6.0972233 = fieldWeight in 992, product of:
      1.0 = tf(freq=1.0), with freq of:
        1.0 = termFreq=1.0
      9.755557 = idf(docFreq=6, maxDocs=44421)
      0.625 = fieldNorm(doc=992)
  2. Agarwal, M.L.; Sharma, S.G.: Classificatory language : an artificial / technical language (1994) 4.88 
    4.8777785 = sum of:
  4.8777785 = weight(author_txt:agarwal in 518) [ClassicSimilarity], result of:
    4.8777785 = fieldWeight in 518, product of:
      1.0 = tf(freq=1.0), with freq of:
        1.0 = termFreq=1.0
      9.755557 = idf(docFreq=6, maxDocs=44421)
      0.5 = fieldNorm(doc=518)
  3. Agarwal, N.K.; Xu, Y.(C.); Poo, D.C.C.: ¬A context-based investigation into source use by information seekers (2011) 3.66 
    3.6583338 = sum of:
  3.6583338 = weight(author_txt:agarwal in 462) [ClassicSimilarity], result of:
    3.6583338 = fieldWeight in 462, product of:
      1.0 = tf(freq=1.0), with freq of:
        1.0 = termFreq=1.0
      9.755557 = idf(docFreq=6, maxDocs=44421)
      0.375 = fieldNorm(doc=462)
  4. Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016) 3.05 
    3.0486116 = sum of:
  3.0486116 = weight(author_txt:agarwal in 4188) [ClassicSimilarity], result of:
    3.0486116 = fieldWeight in 4188, product of:
      1.0 = tf(freq=1.0), with freq of:
        1.0 = termFreq=1.0
      9.755557 = idf(docFreq=6, maxDocs=44421)
      0.3125 = fieldNorm(doc=4188)
  5. Brown, T.B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D.M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; Amodei, D.: Language models are few-shot learners (2020) 1.22 
    1.2194446 = sum of:
  1.2194446 = weight(author_txt:agarwal in 1873) [ClassicSimilarity], result of:
    1.2194446 = fieldWeight in 1873, product of:
      1.0 = tf(freq=1.0), with freq of:
        1.0 = termFreq=1.0
      9.755557 = idf(docFreq=6, maxDocs=44421)
      0.125 = fieldNorm(doc=1873)

Similar documents (content)

  1. Yu, C.; Xue, H.; An, L.; Li, G.: ¬A lightweight semantic-enhanced interactive network for efficient short-text matching (2023) 0.24 
    0.24408808 = sum of:
  0.24408808 = product of:
    0.67802244 = sum of:
      0.031859938 = weight(abstract_txt:semantic in 1891) [ClassicSimilarity], result of:
        0.031859938 = score(doc=1891,freq=3.0), product of:
          0.06577437 = queryWeight, product of:
            1.0219293 = boost
            4.4745317 = idf(docFreq=1375, maxDocs=44421)
            0.0143842865 = queryNorm
          0.48438224 = fieldWeight in 1891, product of:
            1.7320508 = tf(freq=3.0), with freq of:
              3.0 = termFreq=3.0
            4.4745317 = idf(docFreq=1375, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.020547358 = weight(abstract_txt:existing in 1891) [ClassicSimilarity], result of:
        0.020547358 = score(doc=1891,freq=1.0), product of:
          0.070811614 = queryWeight, product of:
            1.060339 = boost
            4.6427093 = idf(docFreq=1162, maxDocs=44421)
            0.0143842865 = queryNorm
          0.29016933 = fieldWeight in 1891, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.6427093 = idf(docFreq=1162, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.0076814694 = weight(abstract_txt:that in 1891) [ClassicSimilarity], result of:
        0.0076814694 = score(doc=1891,freq=2.0), product of:
          0.03674769 = queryWeight, product of:
            1.0802455 = boost
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.0143842865 = queryNorm
          0.20903271 = fieldWeight in 1891, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.0800744 = weight(abstract_txt:short in 1891) [ClassicSimilarity], result of:
        0.0800744 = score(doc=1891,freq=4.0), product of:
          0.11046965 = queryWeight, product of:
            1.324384 = boost
            5.7988343 = idf(docFreq=365, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7248543 = fieldWeight in 1891, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            5.7988343 = idf(docFreq=365, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.019457744 = weight(abstract_txt:model in 1891) [ClassicSimilarity], result of:
        0.019457744 = score(doc=1891,freq=1.0), product of:
          0.078167446 = queryWeight, product of:
            1.3644292 = boost
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0143842865 = queryNorm
          0.24892388 = fieldWeight in 1891, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.049777947 = weight(abstract_txt:text in 1891) [ClassicSimilarity], result of:
        0.049777947 = score(doc=1891,freq=6.0), product of:
          0.08046465 = queryWeight, product of:
            1.3843333 = boost
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0143842865 = queryNorm
          0.61863124 = fieldWeight in 1891, product of:
            2.4494898 = tf(freq=6.0), with freq of:
              6.0 = termFreq=6.0
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.02994201 = weight(abstract_txt:approaches in 1891) [ClassicSimilarity], result of:
        0.02994201 = score(doc=1891,freq=1.0), product of:
          0.10418812 = queryWeight, product of:
            1.5752417 = boost
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0143842865 = queryNorm
          0.2873841 = fieldWeight in 1891, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.057415806 = weight(abstract_txt:network in 1891) [ClassicSimilarity], result of:
        0.057415806 = score(doc=1891,freq=2.0), product of:
          0.14048226 = queryWeight, product of:
            2.112118 = boost
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0143842865 = queryNorm
          0.40870503 = fieldWeight in 1891, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
      0.38126576 = weight(abstract_txt:paraphrase in 1891) [ClassicSimilarity], result of:
        0.38126576 = score(doc=1891,freq=1.0), product of:
          0.6253105 = queryWeight, product of:
            4.456104 = boost
            9.755557 = idf(docFreq=6, maxDocs=44421)
            0.0143842865 = queryNorm
          0.6097223 = fieldWeight in 1891, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.755557 = idf(docFreq=6, maxDocs=44421)
            0.0625 = fieldNorm(doc=1891)
    0.36 = coord(9/25)
  2. Karpathy, A.; Fei-Fei, L.: Deep visual-semantic alignments for generating image descriptions (2015) 0.23 
    0.22608234 = sum of:
  0.22608234 = product of:
    0.7065073 = sum of:
      0.09787321 = weight(abstract_txt:convolutional in 2868) [ClassicSimilarity], result of:
        0.09787321 = score(doc=2868,freq=1.0), product of:
          0.13711755 = queryWeight, product of:
            1.0433354 = boost
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.0143842865 = queryNorm
          0.71379054 = fieldWeight in 2868, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.013579047 = weight(abstract_txt:that in 2868) [ClassicSimilarity], result of:
        0.013579047 = score(doc=2868,freq=4.0), product of:
          0.03674769 = queryWeight, product of:
            1.0802455 = boost
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.0143842865 = queryNorm
          0.3695211 = fieldWeight in 2868, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.04864436 = weight(abstract_txt:model in 2868) [ClassicSimilarity], result of:
        0.04864436 = score(doc=2868,freq=4.0), product of:
          0.078167446 = queryWeight, product of:
            1.3644292 = boost
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0143842865 = queryNorm
          0.6223097 = fieldWeight in 2868, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.025402201 = weight(abstract_txt:text in 2868) [ClassicSimilarity], result of:
        0.025402201 = score(doc=2868,freq=1.0), product of:
          0.08046465 = queryWeight, product of:
            1.3843333 = boost
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0143842865 = queryNorm
          0.3156939 = fieldWeight in 2868, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.124550186 = weight(abstract_txt:sentences in 2868) [ClassicSimilarity], result of:
        0.124550186 = score(doc=2868,freq=2.0), product of:
          0.1610201 = queryWeight, product of:
            1.5989412 = boost
            7.000987 = idf(docFreq=109, maxDocs=44421)
            0.0143842865 = queryNorm
          0.77350706 = fieldWeight in 2868, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            7.000987 = idf(docFreq=109, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.050748885 = weight(abstract_txt:network in 2868) [ClassicSimilarity], result of:
        0.050748885 = score(doc=2868,freq=1.0), product of:
          0.14048226 = queryWeight, product of:
            2.112118 = boost
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0143842865 = queryNorm
          0.36124763 = fieldWeight in 2868, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.12371077 = weight(abstract_txt:sentence in 2868) [ClassicSimilarity], result of:
        0.12371077 = score(doc=2868,freq=1.0), product of:
          0.23118657 = queryWeight, product of:
            2.3464935 = boost
            6.849437 = idf(docFreq=127, maxDocs=44421)
            0.0143842865 = queryNorm
          0.53511226 = fieldWeight in 2868, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            6.849437 = idf(docFreq=127, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
      0.22199866 = weight(abstract_txt:neural in 2868) [ClassicSimilarity], result of:
        0.22199866 = score(doc=2868,freq=3.0), product of:
          0.23671044 = queryWeight, product of:
            2.3743613 = boost
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0143842865 = queryNorm
          0.93784904 = fieldWeight in 2868, product of:
            1.7320508 = tf(freq=3.0), with freq of:
              3.0 = termFreq=3.0
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.078125 = fieldNorm(doc=2868)
    0.32 = coord(8/25)
  3. Mao, J.; Xu, W.; Yang, Y.; Wang, J.; Yuille, A.L.: Explain images with multimodal recurrent neural networks (2014) 0.22 
    0.2179636 = sum of:
  0.2179636 = product of:
    0.7784414 = sum of:
      0.09787321 = weight(abstract_txt:convolutional in 2557) [ClassicSimilarity], result of:
        0.09787321 = score(doc=2557,freq=1.0), product of:
          0.13711755 = queryWeight, product of:
            1.0433354 = boost
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.0143842865 = queryNorm
          0.71379054 = fieldWeight in 2557, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.05957693 = weight(abstract_txt:model in 2557) [ClassicSimilarity], result of:
        0.05957693 = score(doc=2557,freq=6.0), product of:
          0.078167446 = queryWeight, product of:
            1.3644292 = boost
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7621706 = fieldWeight in 2557, product of:
            2.4494898 = tf(freq=6.0), with freq of:
              6.0 = termFreq=6.0
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.10356949 = weight(abstract_txt:deep in 2557) [ClassicSimilarity], result of:
        0.10356949 = score(doc=2557,freq=2.0), product of:
          0.14238746 = queryWeight, product of:
            1.5035862 = boost
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7273779 = fieldWeight in 2557, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.124550186 = weight(abstract_txt:sentences in 2557) [ClassicSimilarity], result of:
        0.124550186 = score(doc=2557,freq=2.0), product of:
          0.1610201 = queryWeight, product of:
            1.5989412 = boost
            7.000987 = idf(docFreq=109, maxDocs=44421)
            0.0143842865 = queryNorm
          0.77350706 = fieldWeight in 2557, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            7.000987 = idf(docFreq=109, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.08789964 = weight(abstract_txt:network in 2557) [ClassicSimilarity], result of:
        0.08789964 = score(doc=2557,freq=3.0), product of:
          0.14048226 = queryWeight, product of:
            2.112118 = boost
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0143842865 = queryNorm
          0.6256992 = fieldWeight in 2557, product of:
            1.7320508 = tf(freq=3.0), with freq of:
              3.0 = termFreq=3.0
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.12371077 = weight(abstract_txt:sentence in 2557) [ClassicSimilarity], result of:
        0.12371077 = score(doc=2557,freq=1.0), product of:
          0.23118657 = queryWeight, product of:
            2.3464935 = boost
            6.849437 = idf(docFreq=127, maxDocs=44421)
            0.0143842865 = queryNorm
          0.53511226 = fieldWeight in 2557, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            6.849437 = idf(docFreq=127, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
      0.18126115 = weight(abstract_txt:neural in 2557) [ClassicSimilarity], result of:
        0.18126115 = score(doc=2557,freq=2.0), product of:
          0.23671044 = queryWeight, product of:
            2.3743613 = boost
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7657505 = fieldWeight in 2557, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.078125 = fieldNorm(doc=2557)
    0.28 = coord(7/25)
  4. Wang, P.; Li, X.: Assessing the quality of information on Wikipedia : a deep-learning approach (2020) 0.20 
    0.19612789 = sum of:
  0.19612789 = product of:
    0.5447997 = sum of:
      0.07829856 = weight(abstract_txt:convolutional in 505) [ClassicSimilarity], result of:
        0.07829856 = score(doc=505,freq=1.0), product of:
          0.13711755 = queryWeight, product of:
            1.0433354 = boost
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.0143842865 = queryNorm
          0.5710324 = fieldWeight in 505, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.1365185 = idf(docFreq=12, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.029058352 = weight(abstract_txt:existing in 505) [ClassicSimilarity], result of:
        0.029058352 = score(doc=505,freq=2.0), product of:
          0.070811614 = queryWeight, product of:
            1.060339 = boost
            4.6427093 = idf(docFreq=1162, maxDocs=44421)
            0.0143842865 = queryNorm
          0.41036138 = fieldWeight in 505, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.6427093 = idf(docFreq=1162, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.0400372 = weight(abstract_txt:short in 505) [ClassicSimilarity], result of:
        0.0400372 = score(doc=505,freq=1.0), product of:
          0.11046965 = queryWeight, product of:
            1.324384 = boost
            5.7988343 = idf(docFreq=365, maxDocs=44421)
            0.0143842865 = queryNorm
          0.36242715 = fieldWeight in 505, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            5.7988343 = idf(docFreq=365, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.019457744 = weight(abstract_txt:model in 505) [ClassicSimilarity], result of:
        0.019457744 = score(doc=505,freq=1.0), product of:
          0.078167446 = queryWeight, product of:
            1.3644292 = boost
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0143842865 = queryNorm
          0.24892388 = fieldWeight in 505, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.02032176 = weight(abstract_txt:text in 505) [ClassicSimilarity], result of:
        0.02032176 = score(doc=505,freq=1.0), product of:
          0.08046465 = queryWeight, product of:
            1.3843333 = boost
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0143842865 = queryNorm
          0.25255513 = fieldWeight in 505, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.10147697 = weight(abstract_txt:deep in 505) [ClassicSimilarity], result of:
        0.10147697 = score(doc=505,freq=3.0), product of:
          0.14238746 = queryWeight, product of:
            1.5035862 = boost
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7126819 = fieldWeight in 505, product of:
            1.7320508 = tf(freq=3.0), with freq of:
              3.0 = termFreq=3.0
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.02994201 = weight(abstract_txt:approaches in 505) [ClassicSimilarity], result of:
        0.02994201 = score(doc=505,freq=1.0), product of:
          0.10418812 = queryWeight, product of:
            1.5752417 = boost
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0143842865 = queryNorm
          0.2873841 = fieldWeight in 505, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.081198215 = weight(abstract_txt:network in 505) [ClassicSimilarity], result of:
        0.081198215 = score(doc=505,freq=4.0), product of:
          0.14048226 = queryWeight, product of:
            2.112118 = boost
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0143842865 = queryNorm
          0.5779962 = fieldWeight in 505, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            4.6239696 = idf(docFreq=1184, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
      0.14500892 = weight(abstract_txt:neural in 505) [ClassicSimilarity], result of:
        0.14500892 = score(doc=505,freq=2.0), product of:
          0.23671044 = queryWeight, product of:
            2.3743613 = boost
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0143842865 = queryNorm
          0.61260045 = fieldWeight in 505, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0625 = fieldNorm(doc=505)
    0.36 = coord(9/25)
  5. Suissa, O.; Elmalech, A.; Zhitomirsky-Geffet, M.: Text analysis using deep neural networks in digital humanities and information science (2022) 0.18 
    0.17923138 = sum of:
  0.17923138 = product of:
    0.56009805 = sum of:
      0.005431619 = weight(abstract_txt:that in 1492) [ClassicSimilarity], result of:
        0.005431619 = score(doc=1492,freq=1.0), product of:
          0.03674769 = queryWeight, product of:
            1.0802455 = boost
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.0143842865 = queryNorm
          0.14780845 = fieldWeight in 1492, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            2.3649352 = idf(docFreq=11344, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.019457744 = weight(abstract_txt:model in 1492) [ClassicSimilarity], result of:
        0.019457744 = score(doc=1492,freq=1.0), product of:
          0.078167446 = queryWeight, product of:
            1.3644292 = boost
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0143842865 = queryNorm
          0.24892388 = fieldWeight in 1492, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            3.9827821 = idf(docFreq=2249, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.028739309 = weight(abstract_txt:text in 1492) [ClassicSimilarity], result of:
        0.028739309 = score(doc=1492,freq=2.0), product of:
          0.08046465 = queryWeight, product of:
            1.3843333 = boost
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0143842865 = queryNorm
          0.3571669 = fieldWeight in 1492, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            4.040882 = idf(docFreq=2122, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.10147697 = weight(abstract_txt:deep in 1492) [ClassicSimilarity], result of:
        0.10147697 = score(doc=1492,freq=3.0), product of:
          0.14238746 = queryWeight, product of:
            1.5035862 = boost
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.0143842865 = queryNorm
          0.7126819 = fieldWeight in 1492, product of:
            1.7320508 = tf(freq=3.0), with freq of:
              3.0 = termFreq=3.0
            6.5834737 = idf(docFreq=166, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.02994201 = weight(abstract_txt:approaches in 1492) [ClassicSimilarity], result of:
        0.02994201 = score(doc=1492,freq=1.0), product of:
          0.10418812 = queryWeight, product of:
            1.5752417 = boost
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0143842865 = queryNorm
          0.2873841 = fieldWeight in 1492, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            4.5981455 = idf(docFreq=1215, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.10253679 = weight(abstract_txt:neural in 1492) [ClassicSimilarity], result of:
        0.10253679 = score(doc=1492,freq=1.0), product of:
          0.23671044 = queryWeight, product of:
            2.3743613 = boost
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0143842865 = queryNorm
          0.43317392 = fieldWeight in 1492, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            6.930783 = idf(docFreq=117, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.18053576 = weight(abstract_txt:detection in 1492) [ClassicSimilarity], result of:
        0.18053576 = score(doc=1492,freq=2.0), product of:
          0.30151528 = queryWeight, product of:
            3.094298 = boost
            6.774214 = idf(docFreq=137, maxDocs=44421)
            0.0143842865 = queryNorm
          0.59876156 = fieldWeight in 1492, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            6.774214 = idf(docFreq=137, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
      0.09197789 = weight(abstract_txt:texts in 1492) [ClassicSimilarity], result of:
        0.09197789 = score(doc=1492,freq=1.0), product of:
          0.26103744 = queryWeight, product of:
            3.2189472 = boost
            5.6376824 = idf(docFreq=429, maxDocs=44421)
            0.0143842865 = queryNorm
          0.35235515 = fieldWeight in 1492, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            5.6376824 = idf(docFreq=429, maxDocs=44421)
            0.0625 = fieldNorm(doc=1492)
    0.32 = coord(8/25)