Academic literature on the topic 'Rocchio classification'

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Journal articles on the topic "Rocchio classification"

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Yang, Wen Chuan, Zhi Dong Shang, and Zhi Cheng Zhang. "Research on MapReduce-Based Rocchio Relevance Feedback in Massive Information Filtering." Advanced Materials Research 962-965 (June 2014): 2712–15. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2712.

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Traditional text classification algorithms have vital impact on information filtering. However, their performances were confined to a large extent in terms of the massive data set. This paper proposes an approach using MapReduce-based Rocchio relevance feedback algorithm, which improved the traditional Rocchio algorithm in the MapReduce paradigm, to resolve the problem of massive information filtering. The experiments on Hadoop cluster showed an effective improvement in performance by using the new method.
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Mohamed, Elfadil Abdalla, Fathi H. Saad, and Omer I. E. Mohamed. "Effects of Classification Techniques on Medical Reports Classification." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 2 (2014): 4206–21. http://dx.doi.org/10.24297/ijct.v13i2.2906.

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Text classification is the process of assigning pre-defined category labels to documents based on what a classifications has learned from training examples. This paper investigates the partially supervised classification approach in the medical field. The approaches that have been evaluated include Rocchio, Naïve Bayesian (NB), Spy, Support vector machine (SVM), and Expectation Maximization (EM). A combination of these methods has been conducted. The experimental result showed that the combination which uses EM in step 2 is always produces better results than those uses SVM using small set o
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Liu, Su Houn, Hsiu Li Liao, Shih Ming Pi, and Chih Chiang Kao. "Patent Classification Using Hybrid Classifier Systems." Advanced Materials Research 187 (February 2011): 458–63. http://dx.doi.org/10.4028/www.scientific.net/amr.187.458.

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Patents are distributed through hundreds of collections, divided up by general area. A hybrid classifier system thus can be a powerful solution to difficult patent classification problems. In this study, we present a system for classifying patent documents on a hybrid approach by combining multiple text classifiers (Naïve Bayes, KNN and Rocchio). Decisions made by various text classifiers can be combined by voting and sampling mechanisms in the system. A prototype system was developed and tested in a real world task. The results have indicated that the accuracy of the hybrid approach is more s
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Vasudevan, Shriram K., Sini Raj Pulari, and C. P. Saranya. "An efficient crop yield prediction using Bootstrap Aggregative MapReduce Rocchio Classification." International Journal of Sustainable Agricultural Management and Informatics 7, no. 2 (2021): 1. http://dx.doi.org/10.1504/ijsami.2021.10039091.

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Saranya, C. P., Sini Raj Pulari, and Shriram K. Vasudevan. "An efficient crop yield prediction using Bootstrap Aggregative MapReduce Rocchio Classification." International Journal of Sustainable Agricultural Management and Informatics 7, no. 2 (2021): 129. http://dx.doi.org/10.1504/ijsami.2021.116072.

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Andayani, U., D. Arisandi, Misbah Hasugian, M. F. Syahputra, and B. Siregar. "The English Language Scientific Literature Classification Based on Abstract Using Rocchio Algorithm." Journal of Physics: Conference Series 1235 (June 2019): 012059. http://dx.doi.org/10.1088/1742-6596/1235/1/012059.

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Mohammad, Adel Hamdan. "Arabic Text Classification: A Review." Modern Applied Science 13, no. 5 (2019): 88. http://dx.doi.org/10.5539/mas.v13n5p88.

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Text classification is an important topic. The number of electronic documents available on line is massive. Text classification aims to classify documents into a set of predefined categories.  Number of researches conducted on English dataset is great in comparison with number of researches done using Arabic dataset. This research could be considered as reference for most researchers who deal with Arabic dataset. This research used the most well-known algorithms used in text classification with Arabic dataset. Besides that, dataset used in this research is large enough in comparison w
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Yahya, Anwar Ali, Addin Osman, and Mohammad Said El-Bashir. "Rocchio algorithm-based particle initialization mechanism for effective PSO classification of high dimensional data." Swarm and Evolutionary Computation 34 (June 2017): 18–32. http://dx.doi.org/10.1016/j.swevo.2016.11.005.

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Mingqiang, Wu, Furong Chang, and Kui Zhang. "Research on the internal influence factors of the text multi-classification problem." MATEC Web of Conferences 173 (2018): 03072. http://dx.doi.org/10.1051/matecconf/201817303072.

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This paper mainly deals with the classification of text type data. The statistics show that more than 8000 articles have been reached in all kinds of documents retrieved by the optical network. However, there are few papers on the factors that affect the classification of text. The text classification method used is important, but the internal factors sometimes play a great role, and even affect the success or failure of the whole text classification. In order to make up for this deficiency, this paper selects the Rocchio algorithm as the classification method, mainly from the category cluster
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PETERS, CHARLES M. E. E., and CORNELIS H. A. KOSTER. "UNCERTAINTY AND TERM SELECTION IN TEXT CATEGORIZATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, no. 01 (2003): 115–37. http://dx.doi.org/10.1142/s0218488503001977.

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This paper discusses the notion of Uncertainty, which has a prominent place in the theory and experimental practice of modern Physics. It argues that the awareness of Uncertainty may also be of tremendous importance to the field of Information Retrieval, and in particular Text Categorization. As an application of Uncertainty in Text Categorization, a new criterion for Term Selection is described, which is based on the Uncertainty in Term Frequency across categories. This criterion allows to distinguish between low-quality (or "noisy") and high-quality ("stiff") terms. We describe an experiment
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Dissertations / Theses on the topic "Rocchio classification"

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Blein, Florent. "Automatic Document Classification Applied to Swedish News." Thesis, Linköping University, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-3065.

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<p>The first part of this paper presents briefly the ELIN[1] system, an electronic newspaper project. ELIN is a framework that stores news and displays them to the end-user. Such news are formatted using the xml[2] format. The project partner Corren[3] provided ELIN with xml articles, however the format used was not the same. My first task has been to develop a software that converts the news from one xml format (Corren) to another (ELIN).</p><p>The second and main part addresses the problem of automatic document classification and tries to find a solution for a specific issue. The goal is to
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Albitar, Shereen. "De l'usage de la sémantique dans la classification supervisée de textes : application au domaine médical." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4343/document.

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Cette thèse porte sur l’impact de l’usage de la sémantique dans le processus de la classification supervisée de textes. Cet impact est évalué au travers d’une étude expérimentale sur des documents issus du domaine médical et en utilisant UMLS (Unified Medical Language System) en tant que ressource sémantique. Cette évaluation est faite selon quatre scénarii expérimentaux d’ajout de sémantique à plusieurs niveaux du processus de classification. Le premier scénario correspond à la conceptualisation où le texte est enrichi avant indexation par des concepts correspondant dans UMLS ; le deuxième et
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Krishnan, Sharenya. "Text-Based Information Retrieval Using Relevance Feedback." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-53603.

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Europeana, a freely accessible digital library with an idea to make Europe's cultural and scientific heritage available to the public was founded by the European Commission in 2008. The goal was to deliver a semantically enriched digital content with multilingual access to it. Even though they managed to increase the content of data they slowly faced the problem of retrieving information in an unstructured form. So to complement the Europeana portal services, ASSETS (Advanced Search Service and Enhanced Technological Solutions) was introduced with services that sought to improve the usability
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Book chapters on the topic "Rocchio classification"

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Zeng, Anping, and Yongping Huang. "A Text Classification Algorithm Based on Rocchio and Hierarchical Clustering." In Advanced Intelligent Computing. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24728-6_59.

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Xu, Xin, Bofeng Zhang, and Qiuxi Zhong. "Text Categorization Using SVMs with Rocchio Ensemble for Internet Information Classification." In Networking and Mobile Computing. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11534310_107.

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Mantrach, Amin, and Jean-Michel Renders. "Extension of the Rocchio Classification Method to Multi-modal Categorization of Documents in Social Media." In Machine Learning and Knowledge Discovery in Databases. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33460-3_14.

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Conference papers on the topic "Rocchio classification"

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Albitar, Shereen, Sebastien Fournier, and Bernard Espinasse. "Conceptualization Effects on MEDLINE Documents Classification Using Rocchio Method." In 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2012. http://dx.doi.org/10.1109/wi-iat.2012.210.

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Sowmya B J, Chetan, and K. G. Srinivasa. "Large scale multi-label text classification of a hierarchical dataset using Rocchio algorithm." In 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS). IEEE, 2016. http://dx.doi.org/10.1109/csitss.2016.7779373.

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Nikitha, K. Sri, and G. P. Sajeev. "An Improved Rocciho Algorithm for Music Mood Classification." In 2018 International Conference on Data Science and Engineering (ICDSE). IEEE, 2018. http://dx.doi.org/10.1109/icdse.2018.8527819.

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