Notes:
MontyLingua is a natural language processing (NLP) toolkit that was developed by researchers at the University of Pennsylvania. It is a widely used tool in the field of NLP and has been used in a variety of applications, including language translation, information extraction, and text classification.
MontyLingua is designed to be easy to use and to provide a wide range of NLP capabilities, including tokenization, part-of-speech tagging, parsing, and named entity recognition. It also includes tools for stemming, synonym detection, and word sense disambiguation.
MontyLingua has been developed to be highly accurate and efficient, and it is widely used by researchers and developers in the NLP community. It is available as open-source software, which means that it can be freely downloaded and used by anyone.
MontyLingua is a natural language processing (NLP) toolkit that is designed to analyze and interpret the meaning of text. When you feed raw English text into MontyLingua, it will process the text and generate a semantic interpretation of it.
The semantic interpretation produced by MontyLingua is a representation of the meaning of the text in a formal, structured way that can be understood and processed by a computer. This interpretation is based on the syntax and semantics of the language, and it includes information about the words and phrases used in the text, as well as their relationships to one another.
MontyLingua includes a wide range of NLP tools and algorithms that are used to analyze and interpret the meaning of text, including tokenization, part-of-speech tagging, parsing, and named entity recognition. It is designed to be highly accurate and efficient, and it is widely used by researchers and developers in the NLP community.
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Merged agreement algorithms for domain independent sentiment analysis D Lambov, S Pais, G Dias – Procedia-Social and Behavioral Sciences, 2011 – Elsevier … 14, pp. 313-323. [19]; H. Liu, Montylingua: An end-to-end natural language processor with common sense (2004). URL http://web.media.mit.edu/hugo/montylingua. Corresponding author. Copyright © 2011 Published by Elsevier Ltd. … Cited by 5 Related articles All 4 versions
Attention and intention goals can mediate disruption in human-computer interaction E Arroyo, T Selker – Human-Computer Interaction–INTERACT 2011, 2011 – Springer … behavior. This is used to determine the user cognitive load based on HCI interactions. The TS 5 Montylingua: http://web.media.mit.edu/~hugo/montylingua/ 6 OpenMind: http://www.openmind.org Page 9. 462 E. Arroyo and T. Selker … Cited by 10 Related articles All 13 versions
CPIDR 5.1 User Manual MA Covington – 2012 – ai1.ai.uga.edu … Hillsdale, NJ: Erlbaum. Liu, Hugo (2004) MontyLingua: An end-to-end natural language processor with common sense. http://web.media.mit.edu/~hugo/montylingua. Santorini, Beatrice (1995) Part-of-speech tagging guidelines for the Penn Treebank Project (3rd revision). … Cited by 4 Related articles All 2 versions
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Ontology-based neural network for patent knowledge management in design collaboration AJC Trappey, CV Trappey, TA Chiang… – International Journal of …, 2013 – Taylor & Francis … English. Available from: http://web.media.mit.edu/~hugo/montylingua/) [Accessed 28 December 2011] View all references), is used to tag the parts of speech (POS), chunks, and lemmas in the training knowledge documents. … Cited by 2 Related articles All 7 versions
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Personalized web search based on user conceptual index S Sendhilkumar – 2015 – ir.inflibnet.ac.in … th ACM International Conference on Information and Knowledge Management, McLean, Virginia, pp. 558-565. 103. Liu H. (2004), ‘Monty Lingua’, http://web.media.mit.edu/~hugo/ montylingua/doc/MontyLingua, accessed latest by March 2006. 104. … Related articles
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Exploiting the query expansion through knowledgebases for images J Jaafar – Visual Informatics: Sustaining Research and …, 2011 – Springer … Arabic question/answering. International Journal on Information and Communication Technologies 3(3), 37–51 (2010) 24. http://web.media.mit.edu/~hugo/montylingua/ 25. http://en.wikipedia.org/wiki/MontyLingua 26. Nasraoui, O … Related articles All 3 versions
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Advanced Knowledge Extraction from WebPages using Natural Language Processing SR Bhat, AK Tripathy, D George, R Jose, R Pinto – Citeseer … In proceedings of the 11th Annual Conference on Computational Learning Theory. ACM, 1998. [15] Hugo Liu, MontyLingua 2.1, NLP software package, available at http://web.media. mit.edu/~hugo/montylingua/ (Accessed on January 12, 2011. Related articles All 3 versions
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Automatic Discovery of Word Semantic Relations G Dias, R Moraliyski, J Cordeiro, A Doucet… – 2010 – sci-gems.math.bas.bg … [15] Hugo Liu. Montylingua: An end-to-end natural lan- guage processor with common sense., 2004. Available at: web.media.mit.edu/~hugo/montylingua. [16] Herbert Rubenstein and John B. Goodenough. Contextual correlates of synonymy. … Related articles All 2 versions
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Concept Based Representations as Complement of Bag of Words in Information Retrieval M Carrillo, A López-López – Artificial Intelligence Applications and …, 2010 – Springer … Nature 222, 960–962 (1969) 16. Liu, Hugo: MontyLingua: An end-to-end natural language processor with common sense (2004), http://web.media.mit.edu/hugo/montylingua 17. Croft, WB, Turtle, HR, Lewis, DD: The use of phrases and structured queries in information retrieval. … Cited by 1 Related articles All 8 versions
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Learning to Rank Effective Paraphrases from Query Logs for Community Question Answering. A Figueroa, G Neumann – AAAI, 2013 – Citeseer … The “number-of” frequency counts are associated with each paraphrase. We exploit semantic relations provided by WordNet such as hypernyms (eg, “hardware ?store”), hyponyms 3http://lucene.apache.org/ 4Using http://web.media.mit.edu/?hugo/montylingua/ Page 4. … Cited by 4 Related articles All 5 versions
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Document filter based on extracted concepts E Varga, B Furlan, V Milutinovic – IPSI Transaction on Internet …, 2010 – internetjournals.net … University. http://nlp.stanford.edu/software/lex-parser.shtml, 25/6/2008. [29] H. Liu, “Montylingua a free, commonsense enriched natural language understander for English,” http://web.media.mit.edu/hugo/montylingua/, 2004. [30 … Cited by 4 Related articles All 7 versions
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