Document (#42045)

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) 6.18
    6.176928 = sum of:
      6.176928 = weight(author_txt:agarwal in 993) [ClassicSimilarity], result of:
        6.176928 = score(doc=993,freq=1.0), product of:
          0.99999994 = queryWeight, product of:
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.101182975 = queryNorm
          6.1769285 = fieldWeight in 993, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.625 = fieldNorm(doc=993)
    
  2. Agarwal, M.L.; Sharma, S.G.: Classificatory language : an artificial / technical language (1994) 4.94
    4.941542 = sum of:
      4.941542 = weight(author_txt:agarwal in 1519) [ClassicSimilarity], result of:
        4.941542 = score(doc=1519,freq=1.0), product of:
          0.99999994 = queryWeight, product of:
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.101182975 = queryNorm
          4.9415426 = fieldWeight in 1519, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.5 = fieldNorm(doc=1519)
    
  3. Agarwal, N.K.; Xu, Y.(C.); Poo, D.C.C.: ¬A context-based investigation into source use by information seekers (2011) 3.71
    3.7061567 = sum of:
      3.7061567 = weight(author_txt:agarwal in 927) [ClassicSimilarity], result of:
        3.7061567 = score(doc=927,freq=1.0), product of:
          0.99999994 = queryWeight, product of:
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.101182975 = queryNorm
          3.706157 = fieldWeight in 927, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.375 = fieldNorm(doc=927)
    
  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) 3.09
    3.088464 = sum of:
      3.088464 = weight(author_txt:agarwal in 4653) [ClassicSimilarity], result of:
        3.088464 = score(doc=4653,freq=1.0), product of:
          0.99999994 = queryWeight, product of:
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.101182975 = queryNorm
          3.0884643 = fieldWeight in 4653, product of:
            1.0 = tf(freq=1.0), with freq of:
              1.0 = termFreq=1.0
            9.883085 = idf(docFreq=5, maxDocs=43254)
            0.3125 = fieldNorm(doc=4653)
    

Similar documents (content)

  1. Karpathy, A.; Fei-Fei, L.: Deep visual-semantic alignments for generating image descriptions (2015) 0.23
    0.22567056 = sum of:
      0.22567056 = product of:
        0.7052205 = sum of:
          0.10081134 = weight(abstract_txt:convolutional in 3333) [ClassicSimilarity], result of:
            0.10081134 = score(doc=3333,freq=1.0), product of:
              0.13909584 = queryWeight, product of:
                1.0420898 = boost
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.014388111 = queryNorm
              0.7247617 = fieldWeight in 3333, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.013711225 = weight(abstract_txt:that in 3333) [ClassicSimilarity], result of:
            0.013711225 = score(doc=3333,freq=4.0), product of:
              0.036786806 = queryWeight, product of:
                1.0718255 = boost
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.014388111 = queryNorm
              0.37272128 = fieldWeight in 3333, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.048767027 = weight(abstract_txt:model in 3333) [ClassicSimilarity], result of:
            0.048767027 = score(doc=3333,freq=4.0), product of:
              0.07787759 = queryWeight, product of:
                1.3505633 = boost
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.014388111 = queryNorm
              0.62620103 = fieldWeight in 3333, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.02515914 = weight(abstract_txt:text in 3333) [ClassicSimilarity], result of:
            0.02515914 = score(doc=3333,freq=1.0), product of:
              0.07952045 = queryWeight, product of:
                1.3647343 = boost
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.014388111 = queryNorm
              0.31638578 = fieldWeight in 3333, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.12260495 = weight(abstract_txt:sentences in 3333) [ClassicSimilarity], result of:
            0.12260495 = score(doc=3333,freq=2.0), product of:
              0.15848199 = queryWeight, product of:
                1.573088 = boost
                7.002016 = idf(docFreq=106, maxDocs=43254)
                0.014388111 = queryNorm
              0.7736207 = fieldWeight in 3333, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                7.002016 = idf(docFreq=106, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.050014947 = weight(abstract_txt:network in 3333) [ClassicSimilarity], result of:
            0.050014947 = score(doc=3333,freq=1.0), product of:
              0.1383761 = queryWeight, product of:
                2.0787804 = boost
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.014388111 = queryNorm
              0.3614421 = fieldWeight in 3333, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.12157012 = weight(abstract_txt:sentence in 3333) [ClassicSimilarity], result of:
            0.12157012 = score(doc=3333,freq=1.0), product of:
              0.2272826 = queryWeight, product of:
                2.3072348 = boost
                6.8465314 = idf(docFreq=124, maxDocs=43254)
                0.014388111 = queryNorm
              0.5348853 = fieldWeight in 3333, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                6.8465314 = idf(docFreq=124, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
          0.22258177 = weight(abstract_txt:neural in 3333) [ClassicSimilarity], result of:
            0.22258177 = score(doc=3333,freq=3.0), product of:
              0.23584913 = queryWeight, product of:
                2.3503137 = boost
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.014388111 = queryNorm
              0.94374645 = fieldWeight in 3333, product of:
                1.7320508 = tf(freq=3.0), with freq of:
                  3.0 = termFreq=3.0
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.078125 = fieldNorm(doc=3333)
        0.32 = coord(8/25)
    
  2. Mao, J.; Xu, W.; Yang, Y.; Wang, J.; Yuille, A.L.: Explain images with multimodal recurrent neural networks (2014) 0.22
    0.21842043 = sum of:
      0.21842043 = product of:
        0.780073 = sum of:
          0.10081134 = weight(abstract_txt:convolutional in 3022) [ClassicSimilarity], result of:
            0.10081134 = score(doc=3022,freq=1.0), product of:
              0.13909584 = queryWeight, product of:
                1.0420898 = boost
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.014388111 = queryNorm
              0.7247617 = fieldWeight in 3022, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.05972717 = weight(abstract_txt:model in 3022) [ClassicSimilarity], result of:
            0.05972717 = score(doc=3022,freq=6.0), product of:
              0.07787759 = queryWeight, product of:
                1.3505633 = boost
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.014388111 = queryNorm
              0.76693654 = fieldWeight in 3022, product of:
                2.4494898 = tf(freq=6.0), with freq of:
                  6.0 = termFreq=6.0
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.10699371 = weight(abstract_txt:deep in 3022) [ClassicSimilarity], result of:
            0.10699371 = score(doc=3022,freq=2.0), product of:
              0.14472605 = queryWeight, product of:
                1.503268 = boost
                6.6912384 = idf(docFreq=145, maxDocs=43254)
                0.014388111 = queryNorm
              0.7392844 = fieldWeight in 3022, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                6.6912384 = idf(docFreq=145, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.12260495 = weight(abstract_txt:sentences in 3022) [ClassicSimilarity], result of:
            0.12260495 = score(doc=3022,freq=2.0), product of:
              0.15848199 = queryWeight, product of:
                1.573088 = boost
                7.002016 = idf(docFreq=106, maxDocs=43254)
                0.014388111 = queryNorm
              0.7736207 = fieldWeight in 3022, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                7.002016 = idf(docFreq=106, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.08662842 = weight(abstract_txt:network in 3022) [ClassicSimilarity], result of:
            0.08662842 = score(doc=3022,freq=3.0), product of:
              0.1383761 = queryWeight, product of:
                2.0787804 = boost
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.014388111 = queryNorm
              0.626036 = fieldWeight in 3022, product of:
                1.7320508 = tf(freq=3.0), with freq of:
                  3.0 = termFreq=3.0
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.12157012 = weight(abstract_txt:sentence in 3022) [ClassicSimilarity], result of:
            0.12157012 = score(doc=3022,freq=1.0), product of:
              0.2272826 = queryWeight, product of:
                2.3072348 = boost
                6.8465314 = idf(docFreq=124, maxDocs=43254)
                0.014388111 = queryNorm
              0.5348853 = fieldWeight in 3022, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                6.8465314 = idf(docFreq=124, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
          0.18173726 = weight(abstract_txt:neural in 3022) [ClassicSimilarity], result of:
            0.18173726 = score(doc=3022,freq=2.0), product of:
              0.23584913 = queryWeight, product of:
                2.3503137 = boost
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.014388111 = queryNorm
              0.77056575 = fieldWeight in 3022, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.078125 = fieldNorm(doc=3022)
        0.28 = coord(7/25)
    
  3. Wang, P.; Li, X.: Assessing the quality of information on Wikipedia : a deep-learning approach (2020) 0.20
    0.19793703 = sum of:
      0.19793703 = product of:
        0.5498251 = sum of:
          0.08064907 = weight(abstract_txt:convolutional in 506) [ClassicSimilarity], result of:
            0.08064907 = score(doc=506,freq=1.0), product of:
              0.13909584 = queryWeight, product of:
                1.0420898 = boost
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.014388111 = queryNorm
              0.57980937 = fieldWeight in 506, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                9.27695 = idf(docFreq=10, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.029424703 = weight(abstract_txt:existing in 506) [ClassicSimilarity], result of:
            0.029424703 = score(doc=506,freq=2.0), product of:
              0.07102141 = queryWeight, product of:
                1.0530711 = boost
                4.6873546 = idf(docFreq=1082, maxDocs=43254)
                0.014388111 = queryNorm
              0.4143075 = fieldWeight in 506, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                4.6873546 = idf(docFreq=1082, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.039589323 = weight(abstract_txt:short in 506) [ClassicSimilarity], result of:
            0.039589323 = score(doc=506,freq=1.0), product of:
              0.10905442 = queryWeight, product of:
                1.3049225 = boost
                5.808377 = idf(docFreq=352, maxDocs=43254)
                0.014388111 = queryNorm
              0.36302355 = fieldWeight in 506, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                5.808377 = idf(docFreq=352, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.01950681 = weight(abstract_txt:model in 506) [ClassicSimilarity], result of:
            0.01950681 = score(doc=506,freq=1.0), product of:
              0.07787759 = queryWeight, product of:
                1.3505633 = boost
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.014388111 = queryNorm
              0.2504804 = fieldWeight in 506, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.0076866 = idf(docFreq=2136, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.020127311 = weight(abstract_txt:text in 506) [ClassicSimilarity], result of:
            0.020127311 = score(doc=506,freq=1.0), product of:
              0.07952045 = queryWeight, product of:
                1.3647343 = boost
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.014388111 = queryNorm
              0.25310862 = fieldWeight in 506, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.10483199 = weight(abstract_txt:deep in 506) [ClassicSimilarity], result of:
            0.10483199 = score(doc=506,freq=3.0), product of:
              0.14472605 = queryWeight, product of:
                1.503268 = boost
                6.6912384 = idf(docFreq=145, maxDocs=43254)
                0.014388111 = queryNorm
              0.7243478 = fieldWeight in 506, product of:
                1.7320508 = tf(freq=3.0), with freq of:
                  3.0 = termFreq=3.0
                6.6912384 = idf(docFreq=145, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.03028219 = weight(abstract_txt:approaches in 506) [ClassicSimilarity], result of:
            0.03028219 = score(doc=506,freq=1.0), product of:
              0.10441106 = queryWeight, product of:
                1.5638026 = boost
                4.640457 = idf(docFreq=1134, maxDocs=43254)
                0.014388111 = queryNorm
              0.29002857 = fieldWeight in 506, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.640457 = idf(docFreq=1134, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.080023915 = weight(abstract_txt:network in 506) [ClassicSimilarity], result of:
            0.080023915 = score(doc=506,freq=4.0), product of:
              0.1383761 = queryWeight, product of:
                2.0787804 = boost
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.014388111 = queryNorm
              0.57830733 = fieldWeight in 506, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                4.6264586 = idf(docFreq=1150, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
          0.1453898 = weight(abstract_txt:neural in 506) [ClassicSimilarity], result of:
            0.1453898 = score(doc=506,freq=2.0), product of:
              0.23584913 = queryWeight, product of:
                2.3503137 = boost
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.014388111 = queryNorm
              0.6164526 = fieldWeight in 506, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                6.9743648 = idf(docFreq=109, maxDocs=43254)
                0.0625 = fieldNorm(doc=506)
        0.36 = coord(9/25)
    
  4. Gipp, B.; Meuschke, N.; Breitinger, C.: Citation-based plagiarism detection : practicability on a large-scale scientific corpus (2014) 0.19
    0.18739444 = sum of:
      0.18739444 = product of:
        0.66926587 = sum of:
          0.21379879 = weight(abstract_txt:plagiarism in 4797) [ClassicSimilarity], result of:
            0.21379879 = score(doc=4797,freq=9.0), product of:
              0.12808666 = queryWeight, product of:
                8.902256 = idf(docFreq=15, maxDocs=43254)
                0.014388111 = queryNorm
              1.669173 = fieldWeight in 4797, product of:
                3.0 = tf(freq=9.0), with freq of:
                  9.0 = termFreq=9.0
                8.902256 = idf(docFreq=15, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.018225467 = weight(abstract_txt:semantic in 4797) [ClassicSimilarity], result of:
            0.018225467 = score(doc=4797,freq=1.0), product of:
              0.0650195 = queryWeight, product of:
                1.0075924 = boost
                4.484923 = idf(docFreq=1325, maxDocs=43254)
                0.014388111 = queryNorm
              0.28030768 = fieldWeight in 4797, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                4.484923 = idf(docFreq=1325, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.00548449 = weight(abstract_txt:that in 4797) [ClassicSimilarity], result of:
            0.00548449 = score(doc=4797,freq=1.0), product of:
              0.036786806 = queryWeight, product of:
                1.0718255 = boost
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.014388111 = queryNorm
              0.14908852 = fieldWeight in 4797, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.012468874 = weight(abstract_txt:study in 4797) [ClassicSimilarity], result of:
            0.012468874 = score(doc=4797,freq=1.0), product of:
              0.057788286 = queryWeight, product of:
                1.1633987 = boost
                3.4522913 = idf(docFreq=3723, maxDocs=43254)
                0.014388111 = queryNorm
              0.2157682 = fieldWeight in 4797, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                3.4522913 = idf(docFreq=3723, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.028464317 = weight(abstract_txt:text in 4797) [ClassicSimilarity], result of:
            0.028464317 = score(doc=4797,freq=2.0), product of:
              0.07952045 = queryWeight, product of:
                1.3647343 = boost
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.014388111 = queryNorm
              0.35794964 = fieldWeight in 4797, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.052450288 = weight(abstract_txt:approaches in 4797) [ClassicSimilarity], result of:
            0.052450288 = score(doc=4797,freq=3.0), product of:
              0.10441106 = queryWeight, product of:
                1.5638026 = boost
                4.640457 = idf(docFreq=1134, maxDocs=43254)
                0.014388111 = queryNorm
              0.5023442 = fieldWeight in 4797, product of:
                1.7320508 = tf(freq=3.0), with freq of:
                  3.0 = termFreq=3.0
                4.640457 = idf(docFreq=1134, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
          0.33837366 = weight(abstract_txt:detection in 4797) [ClassicSimilarity], result of:
            0.33837366 = score(doc=4797,freq=7.0), product of:
              0.30026147 = queryWeight, product of:
                3.0621598 = boost
                6.8150325 = idf(docFreq=128, maxDocs=43254)
                0.014388111 = queryNorm
              1.12693 = fieldWeight in 4797, product of:
                2.6457512 = tf(freq=7.0), with freq of:
                  7.0 = termFreq=7.0
                6.8150325 = idf(docFreq=128, maxDocs=43254)
                0.0625 = fieldNorm(doc=4797)
        0.28 = coord(7/25)
    
  5. AL-Smadi, M.; Jaradat, Z.; AL-Ayyoub, M.; Jararweh, Y.: Paraphrase identification and semantic text similarity analysis in Arabic news tweets using lexical, syntactic, and semantic features (2017) 0.18
    0.18178967 = sum of:
      0.18178967 = product of:
        0.75745696 = sum of:
          0.031567432 = weight(abstract_txt:semantic in 96) [ClassicSimilarity], result of:
            0.031567432 = score(doc=96,freq=3.0), product of:
              0.0650195 = queryWeight, product of:
                1.0075924 = boost
                4.484923 = idf(docFreq=1325, maxDocs=43254)
                0.014388111 = queryNorm
              0.48550713 = fieldWeight in 96, product of:
                1.7320508 = tf(freq=3.0), with freq of:
                  3.0 = termFreq=3.0
                4.484923 = idf(docFreq=1325, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
          0.00775624 = weight(abstract_txt:that in 96) [ClassicSimilarity], result of:
            0.00775624 = score(doc=96,freq=2.0), product of:
              0.036786806 = queryWeight, product of:
                1.0718255 = boost
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.014388111 = queryNorm
              0.210843 = fieldWeight in 96, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                2.3854163 = idf(docFreq=10822, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
          0.03474646 = weight(abstract_txt:good in 96) [ClassicSimilarity], result of:
            0.03474646 = score(doc=96,freq=1.0), product of:
              0.0999689 = queryWeight, product of:
                1.2493829 = boost
                5.561163 = idf(docFreq=451, maxDocs=43254)
                0.014388111 = queryNorm
              0.34757268 = fieldWeight in 96, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                5.561163 = idf(docFreq=451, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
          0.040254623 = weight(abstract_txt:text in 96) [ClassicSimilarity], result of:
            0.040254623 = score(doc=96,freq=4.0), product of:
              0.07952045 = queryWeight, product of:
                1.3647343 = boost
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.014388111 = queryNorm
              0.50621724 = fieldWeight in 96, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                4.049738 = idf(docFreq=2048, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
          0.09151683 = weight(abstract_txt:texts in 96) [ClassicSimilarity], result of:
            0.09151683 = score(doc=96,freq=1.0), product of:
              0.2587648 = queryWeight, product of:
                3.1782327 = boost
                5.658688 = idf(docFreq=409, maxDocs=43254)
                0.014388111 = queryNorm
              0.353668 = fieldWeight in 96, product of:
                1.0 = tf(freq=1.0), with freq of:
                  1.0 = termFreq=1.0
                5.658688 = idf(docFreq=409, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
          0.55161536 = weight(abstract_txt:paraphrase in 96) [ClassicSimilarity], result of:
            0.55161536 = score(doc=96,freq=2.0), product of:
              0.6314643 = queryWeight, product of:
                4.4407105 = boost
                9.883085 = idf(docFreq=5, maxDocs=43254)
                0.014388111 = queryNorm
              0.8735496 = fieldWeight in 96, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                9.883085 = idf(docFreq=5, maxDocs=43254)
                0.0625 = fieldNorm(doc=96)
        0.24 = coord(6/25)