-
Damerau, F.J.: Generating an evaluating domain-oriented multi-word terms from texts (1993)
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- Information processing and management. 29(1993) no.4, S.433-447
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Souza, R.R.; Gil-Leiva, I.: Automatic indexing of scientific texts : a methodological comparison (2016)
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- Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
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Vinyals, O.; Toshev, A.; Bengio, S.; Erhan, D.: ¬A picture is worth a thousand (coherent) words : building a natural description of images (2014)
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- Content
- "People can summarize a complex scene in a few words without thinking twice. It's much more difficult for computers. But we've just gotten a bit closer -- we've developed a machine-learning system that can automatically produce captions (like the three above) to accurately describe images the first time it sees them. This kind of system could eventually help visually impaired people understand pictures, provide alternate text for images in parts of the world where mobile connections are slow, and make it easier for everyone to search on Google for images. Recent research has greatly improved object detection, classification, and labeling. But accurately describing a complex scene requires a deeper representation of what's going on in the scene, capturing how the various objects relate to one another and translating it all into natural-sounding language. Many efforts to construct computer-generated natural descriptions of images propose combining current state-of-the-art techniques in both computer vision and natural language processing to form a complete image description approach. But what if we instead merged recent computer vision and language models into a single jointly trained system, taking an image and directly producing a human readable sequence of words to describe it? This idea comes from recent advances in machine translation between languages, where a Recurrent Neural Network (RNN) transforms, say, a French sentence into a vector representation, and a second RNN uses that vector representation to generate a target sentence in German. Now, what if we replaced that first RNN and its input words with a deep Convolutional Neural Network (CNN) trained to classify objects in images? Normally, the CNN's last layer is used in a final Softmax among known classes of objects, assigning a probability that each object might be in the image. But if we remove that final layer, we can instead feed the CNN's rich encoding of the image into a RNN designed to produce phrases. We can then train the whole system directly on images and their captions, so it maximizes the likelihood that descriptions it produces best match the training descriptions for each image.
-
Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995)
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- Date
- 31. 7.1996 9:22:19
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Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996)
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- Date
- 6. 3.1997 16:22:15
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Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983)
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- 14. 3.1996 13:22:21
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Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997)
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- Source
- International forum on information and documentation. 22(1997) no.1, S.17-28
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Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006)
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- 22. 7.2006 17:32:00
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Hmeidi, I.; Kanaan, G.; Evens, M.: Design and implementation of automatic indexing for information retrieval with Arabic documents (1997)
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- 29. 7.1998 17:40:01
-
Banerjee, K.; Johnson, M.: Improving access to archival collections with automated entity extraction (2015)
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- Source
- Code4Lib journal. Issue 29(2015), [http://journal.code4lib.org/issues/issues/issue29]
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Ward, M.L.: ¬The future of the human indexer (1996)
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- Date
- 9. 2.1997 18:44:22
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Chung, Y.M.; Lee, J.Y.: ¬A corpus-based approach to comparative evaluation of statistical term association measures (2001)
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- 29. 9.2001 14:01:18
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Li, W.; Wong, K.-F.; Yuan, C.: Toward automatic Chinese temporal information extraction (2001)
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- 29. 9.2001 14:02:50
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Li, X.; Zhang, A.; Li, C.; Ouyang, J.; Cai, Y.: Exploring coherent topics by topic modeling with term weighting (2018)
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- 15. 3.2019 18:55:29
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Wang, S.; Koopman, R.: Embed first, then predict (2019)
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- 29. 9.2019 12:18:42
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Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998)
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- 11. 9.2000 19:53:22
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Milstead, J.L.: Thesauri in a full-text world (1998)
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- 22. 9.1997 19:16:05
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Markoff, J.: Researchers announce advance in image-recognition software (2014)
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- Content
- Computer vision specialists said that despite the improvements, these software systems had made only limited progress toward the goal of digitally duplicating human vision and, even more elusive, understanding. "I don't know that I would say this is 'understanding' in the sense we want," said John R. Smith, a senior manager at I.B.M.'s T.J. Watson Research Center in Yorktown Heights, N.Y. "I think even the ability to generate language here is very limited." But the Google and Stanford teams said that they expect to see significant increases in accuracy as they improve their software and train these programs with larger sets of annotated images. A research group led by Tamara L. Berg, a computer scientist at the University of North Carolina at Chapel Hill, is training a neural network with one million images annotated by humans. "You're trying to tell the story behind the image," she said. "A natural scene will be very complex, and you want to pick out the most important objects in the image.""
-
Martins, A.L.; Souza, R.R.; Ribeiro de Mello, H.: ¬The use of noun phrases in information retrieval : proposing a mechanism for automatic classification (2014)
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- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
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Mesquita, L.A.P.; Souza, R.R.; Baracho Porto, R.M.A.: Noun phrases in automatic indexing: : a structural analysis of the distribution of relevant terms in doctoral theses (2014)
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- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
