-
Jiang, Y.; Meng, R.; Huang, Y.; Lu, W.; Liu, J.: Generating keyphrases for readers : a controllable keyphrase generation framework (2023)
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- Abstract
- With the wide application of keyphrases in many Information Retrieval (IR) and Natural Language Processing (NLP) tasks, automatic keyphrase prediction has been emerging. However, these statistically important phrases are contributing increasingly less to the related tasks because the end-to-end learning mechanism enables models to learn the important semantic information of the text directly. Similarly, keyphrases are of little help for readers to quickly grasp the paper's main idea because the relationship between the keyphrase and the paper is not explicit to readers. Therefore, we propose to generate keyphrases with specific functions for readers to bridge the semantic gap between them and the information producers, and verify the effectiveness of the keyphrase function for assisting users' comprehension with a user experiment. A controllable keyphrase generation framework (the CKPG) that uses the keyphrase function as a control code to generate categorized keyphrases is proposed and implemented based on Transformer, BART, and T5, respectively. For the Computer Science domain, the Macro-avgs of , , and on the Paper with Code dataset are up to 0.680, 0.535, and 0.558, respectively. Our experimental results indicate the effectiveness of the CKPG models.
- Date
- 22. 6.2023 14:55:20
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.7, S.759-774
-
Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006)
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- Date
- 22. 7.2006 17:25:48
- Source
- Journal of the American Society for Information Science and Technology. 57(2006) no.6, S.740-752
-
Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016)
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- Date
- 22. 1.2016 12:29:41
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.2, S.366-379
-
Oh, H.; Nam, S.; Zhu, Y.: Structured abstract summarization of scientific articles : summarization using full-text section information (2023)
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- Date
- 22. 1.2023 18:57:12
- Source
- Journal of the Association for Information Science and Technology. 74(2023) no.2, S.234-248
-
Paice, C.D.: Automatic abstracting (1994)
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- Source
- Encyclopedia of library and information science. Vol.53, [=Suppl.16]
-
Pinto, M.: Engineering the production of meta-information : the abstracting concern (2003)
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- Source
- Journal of information science. 29(2003) no.5, S.405-418
-
Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994)
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- Source
- Science. 264(1994), S.1421-1426
-
Craven, T.C.: ¬A computer-aided abstracting tool kit (1993)
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- Source
- Canadian journal of information and library science. 18(1993) no.2, S.20-31
-
Craven, T.C.: ¬A phrase flipper for the assistance of writers of abstracts and other text (1995)
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- Source
- Canadian journal of information and library science. 20(1995) nos.3/4, S.41-49
-
Endres-Niggemeyer, B.; Neugebauer, E.: Professional summarizing : no cognitive simulation without observation (1998)
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- Source
- Journal of the American Society for Information Science. 49(1998) no.6, S.486-506
-
Liu, J.; Wu, Y.; Zhou, L.: ¬A hybrid method for abstracting newspaper articles (1999)
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- Source
- Journal of the American Society for Information Science. 50(1999) no.13, S.1234-1245
-
Yang, C.C.; Wang, F.L.: Hierarchical summarization of large documents (2008)
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- Abstract
- Many automatic text summarization models have been developed in the last decades. Related research in information science has shown that human abstractors extract sentences for summaries based on the hierarchical structure of documents; however, the existing automatic summarization models do not take into account the human abstractor's behavior of sentence extraction and only consider the document as a sequence of sentences during the process of extraction of sentences as a summary. In general, a document exhibits a well-defined hierarchical structure that can be described as fractals - mathematical objects with a high degree of redundancy. In this article, we introduce the fractal summarization model based on the fractal theory. The important information is captured from the source document by exploring the hierarchical structure and salient features of the document. A condensed version of the document that is informatively close to the source document is produced iteratively using the contractive transformation in the fractal theory. The fractal summarization model is the first attempt to apply fractal theory to document summarization. It significantly improves the divergence of information coverage of summary and the precision of summary. User evaluations have been conducted. Results have indicated that fractal summarization is promising and outperforms current summarization techniques that do not consider the hierarchical structure of documents.
- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.6, S.887-902
-
Kim, H.H.; Kim, Y.H.: ERP/MMR algorithm for classifying topic-relevant and topic-irrelevant visual shots of documentary videos (2019)
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- Footnote
- Beitrag in einem 'Special issue on neuro-information science'.
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.9, S.931-941
-
Goh, A.; Hui, S.C.: TES: a text extraction system (1996)
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- Date
- 26. 2.1997 10:22:43
-
Robin, J.; McKeown, K.: Empirically designing and evaluating a new revision-based model for summary generation (1996)
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- Date
- 6. 3.1997 16:22:15
-
Jones, P.A.; Bradbeer, P.V.G.: Discovery of optimal weights in a concept selection system (1996)
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- Source
- Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
-
Xiong, S.; Ji, D.: Query-focused multi-document summarization using hypergraph-based ranking (2016)
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- Content
- Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457315001491.
-
Craven, T.C.: ¬An experiment in the use of tools for computer-assisted abstracting (1996)
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- Source
- Global complexity: information, chaos and control. Proceedings of the 59th Annual Meeting of the American Society for Information Science, ASIS'96, Baltimore, Maryland, 21-24 Oct 1996. Ed.: S. Hardin
-
Moens, M.-F.; Uyttendaele, C.; Dumotier, J.: Abstracting of legal cases : the potential of clustering based on the selection of representative objects (1999)
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- Source
- Journal of the American Society for Information Science. 50(1999) no.2, S.151-161
-
Craven, T.C.: Abstracts produced using computer assistance (2000)
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- Source
- Journal of the American Society for Information Science. 51(2000) no.8, S.745-756
