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1
Robust phoneme recognition for a speech therapy environment
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2
An Enhanced Corpus for Arabic Newspapers Comments
In: ISSN: 1683-3198 ; International Arab Journal of Information Technology ; https://hal.archives-ouvertes.fr/hal-03124728 ; International Arab Journal of Information Technology, Colleges of Computing and Information Society (CCIS), 2020, 17 (5), pp.789-798. ⟨10.34028/iajit/17/5/12⟩ (2020)
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3
Application of Support Vector Machine (SVM) in the Sentiment Analysis of Twitter DataSet
Han; Chien; Chiu...
In: Applied Sciences ; Volume 10 ; Issue 3 (2020)
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4
Furosine and HMF determination in prebiotic-supplemented infant formula from Spanish market
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5
Persian Named Entity Recognition
Dashtipour, K.; Gogate, M.; Adeel, A.. - : Institute of Electrical and Electronics Engineers, 2017
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6
Análisis de sentimientos a nivel de aspecto usando ontologías y aprendizaje automático ; Aspect-based sentiment analysis using ontologies and machine learning
Henriquez Miranda, Carlos; Pla Santamaría, Ferrán; Hurtado Oliver, Lluís Felip. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2017
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7
Persian Named Entity Recognition
Dashtipour, Kia; Gogate, Mandar; Adeel, Ahsan. - : Institute of Electrical and Electronics Engineers Inc, 2017. : Piscataway, NJ, USA, 2017
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8
Modality prediction of biomedical literature images using multimodal feature representation ... : Klassifikation von Bildern der biomedizinischen Literatur unter Anwendung multimodaler Merkmale ...
Pelka, Obioma; Friedrich, Christoph M.. - : German Medical Science GMS Publishing House, 2016
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9
Language identification of multilingual posts from Twitter: a case study
Hurtado Oliver, Lluis Felip; Pla Santamaría, Ferran. - : Springer Verlag (Germany), 2016
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10
Continuous Speech Classification Systems for Voice Pathologies Identification
In: IFIP Advances in Information and Communication Technology ; 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS) ; https://hal.inria.fr/hal-01343485 ; 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2015, Costa de Caparica, Portugal. pp.217-224, ⟨10.1007/978-3-319-16766-4_23⟩ (2015)
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11
Sentiment analysis: text, pre-processing, reader views and cross domains
Haddi, Emma. - : Brunel University London, 2015
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12
A predictive model to detect online cyberbullying
Kasture, Abhijeet Sudhir. - : Auckland University of Technology, 2015
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13
Analysis of Features for Synthetic Aperture Radar Target Classification
In: DTIC (2015)
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14
Virtual sign : a real time bidirectional translator of portuguese sign language
Escudeiro, Paula; Escudeiro, Nuno; Reis, Rosa. - : ScienceDirect, 2015
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15
Οπτική ανίχνευση φωνητικής δραστηριότητας ...
Πατρώνα, Φωτεινή Παύλου. - : Aristotle University of Thessaloniki, 2014
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16
Modelling Psychological Needs for User-dependent Contextual Suggestion
In: DTIC (2014)
Abstract: This paper presents our approach for the Contextual Suggestion track of 2014 Text REtrieval Conference (TREC). The task aims to provide recommendations on points of interests (POI) for various kinds of users under different contexts. This becomes challenging due to the limited amount of training data provided by TREC and the demanding constraints for a suggestion to be judged as relevant. Our approach does not deviate from existing Machine Learning based methods in principle, but sticks closely to the defined relevance judgement criteria, by focusing primarily on modelling users' preferences on POI categories, and investigating upon their psychological expectations on the textual descriptions of the POIs. The latter is considered as our novelty in this work. Support Vector Regression was used for suggestion ranking, an ad-hoc web information extractor was used to collect POI descriptions, and a description evaluation mechanism was engaged to select proper POI descriptions subject to the nature of the POIs. Our results suggest that our methods are effective in obtaining satisfying user-specific POI rankings and generating descriptions that meet users' psychological expectations. ; Presented at the Twenty-Third Text REtrieval Conference (TREC 2014) held in Gaithersburg, Maryland, November 19-21, 2014. The conference was co-sponsored by the National Institute of Standards and Technology (NIST) and the Defense Advanced Research Projects Agency (DARPA).
Keyword: *DATA MINING; *INFORMATION RETRIEVAL; *LEARNING MACHINES; ALGORITHMS; CLASSIFICATION; COMPUTATIONAL LINGUISTICS; CONTEXT; Cybernetics; FEATURE EXTRACTION; Information Science; INFORMATION SYSTEMS; INTELLIGENT INFORMATION SYSTEMS; INTERNET; LBRS(LOCATION BASED RECOMMENDER SYSTEMS); PATTERN RECOGNITION; POI(POINT OF INTEREST); Psychology; RANKING; REGRESSION ANALYSIS; SEMANTICS; SUPPORT VECTOR MACHINES; TEXT MINING; TEXT PROCESSING; USER NEEDS; WEB CRAWLING; WIRELESS COMMUNICATIONS
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA618577
http://www.dtic.mil/docs/citations/ADA618577
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17
Conversion of sign language to Spoken sentences by means of a sensory glove
Cavallo, P; Saggio, G. - : Academy Publisher, 2014
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18
Machine Learning Techniques for Gesture Recognition
Caceres, Carlos Antonio. - : Virginia Tech, 2014
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19
The importance of word-final vowel duration for non-native portuguese speaker identification by means of Support Vector Machines
In: Revista Brasileira de Linguística Aplicada, Vol 14, Iss 3, Pp 689-714 (2014) (2014)
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20
ReaderBench, o platformă integrată pentru analiza complexității textuale și a strategiilor de lectură
In: Proc. 10-a Conf. Nat. de Interactiune Om-Calculator (RoCHI 2013) ; https://hal.archives-ouvertes.fr/hal-01412573 ; Proc. 10-a Conf. Nat. de Interactiune Om-Calculator (RoCHI 2013), T. Stefanut; C. Rusu, 2013, Cluj, Romania. pp.39-46 (2013)
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