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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...32 Hits 1 – 20 of 632 1 ImageSpirit: Verbal guided image parsing Ming-ming Cheng; Shuai Zheng; Wen-yan Lin... In: http://vecg.cs.ucl.ac.uk/Projects/SmartGeometry/image_spirit/paper_docs/imageSpirit_tog_14.pdf (2014) BASE Show details 2 Annals of A Model to Compute Degree of Polarity of Review Titles Sohom Ghosh; Santanu Modak; Abhoy Ch In: http://www.researchmathsci.org/apamart/apam-v7n1-11.pdf (2014) BASE Show details 3 Automatic extraction of property norm-like data from large text corpora Colin Kelly; A Barry Devereux; B Anna Korhonena In: http://www.cl.cam.ac.uk/%7Ealk23/cog-sci-2014.pdf (2013) BASE Show details 4 Unsupervised sentiment analysis with emotional signals Xia Hu; Jiliang Tang; Huiji Gao... In: http://www.public.asu.edu/~xiahu/papers/www13.pdf (2013) BASE Show details 5 Using Empirically Constructed Lexical Resources for Named Entity Recognition. Biomed Inform Insights Siddhartha Jonnalagadda; Trevor Cohen; Stephen Wu... In: http://www.la-press.com/redirect_file.php?fileId%3D5041%26fileType%3Dpdf%26filename%3D3738-BII-Using-Empirically-Constructed-Lexical-Resources-for-Named-Entity-Recog.pdf (2013) BASE Show details 6 Semantic Interpretation of Noun Compounds Using Verbal and Other Paraphrases Preslav I. Nakov In: http://people.ischool.berkeley.edu/~hearst/papers/acm_tslp_2013.pdf (2013) BASE Show details 7 DOI:10.1145/2063576.2063990 A Pretopological Framework for the Automatic Construction of Lexical-Semantic Structures from Texts Guillaume Cleuziou; Davide Buscaldi; Vincent Levorato In: http://hal.inria.fr/docs/00/82/52/32/PDF/cikmpp0705-cleuziou_HAL.pdf (2013) BASE Show details 8 CroNER: Recognizing Named Entities in Croatian Using Conditional Random Fields Mladen Karan; Goran Glavaš; Frane Šarić... In: http://www.informatica.si/PDF/37-2/11_Karan - CroNER Recognizing Named Entities in Croatian Using Conditional Random Fields.pdf (2013) BASE Show details 9 Detection of Naming Convention Violations in Process Models for Different Languages Henrik Leopold; Rami-habib Eid-sabbagh; Jan Mendling... In: http://www.mendling.com/publications/DSS13-Convention.pdf (2013) BASE Show details 10 Learning Sentiment Lexicons in Spanish Verónica Pérez-rosas; Carmen Banea; Rada Mihalcea In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/1081_Paper.pdf (2012) BASE Show details 11 Seeing the Best and Worst of Everything on the Web with a Two-level, Feature-rich Affect Lexicon Tony Veale In: http://www2012.wwwconference.org/proceedings/companion/p623.pdf (2012) Abstract: Affect lexica are useful for sentiment analysis because they map words (or senses) onto sentiment ratings. However, few lexica explain their ratings, or provide sufficient feature richness to allow a selective “spin ” to be placed on a word in context. Since an affect lexicon aims to capture the affect of a word or sense in its most stereotypical usage, it should be grounded in explicit stereotype representations of each word’s most salient properties and behaviors. We show here how to acquire a large stereotype lexicon from Web content, and further show how to determine sentiment ratings for each entry in the lexicon, both at the level of properties and behaviors and at the level of stereotypes. Finally, we show how the properties of a stereotype can be segregated on demand, to place a positive or negative spin on a word in context. Keyword: Categories and Subject Descriptors I.2.7 [Artificial Intelligence; Human Factors; lang. parsing and understanding; Languages. Keywords Affect lexicons; Measurement; Natural Language Processing – language models; text analysis. General Terms Algorithms URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.309.7155 http://www2012.wwwconference.org/proceedings/companion/p623.pdf BASE Hide details 12 Dynamic Units of Visual Speech Sarah L. Taylor; Moshe Mahler; Barry-john Theobald... In: http://www.iainm.com/iainm/visemes_files/sca2012_1.pdf (2012) BASE Show details 13 Collective Search for Concept Disambiguation Anja Pilz; Gerhard Paass In: http://aclweb.org/anthology/C/C12/C12-1137.pdf (2012) BASE Show details 14 Automatic Text Analysis by Artificial Intelligence Dunja Mladenić; Marko Grobelnik In: http://www.informatica.si/PDF/37-1/05_Mladenic-Automatic Text Analysis by Artificial Intell.pdf (2012) BASE Show details 15 R.: WiSeNet: Building a Wikipedia-based semantic network with ontologized relations Andrea Moro In: http://wwwusers.di.uniroma1.it/~navigli/pubs/CIKM_2012_Moro_Navigli.pdf (2012) BASE Show details 16 Alleviating Data Sparsity for Twitter Sentiment Analysis Hassan Saif; Yulan He; Harith Alani In: http://ceur-ws.org/Vol-838/paper_01.pdf (2012) BASE Show details 17 A new model of Time Expressions Detection and Annotation in Vietnamese: The hôm case. In: http://hal.inria.fr/docs/00/76/41/83/PDF/articleIALP2012_SCHWER_LAMBERT_BOFFO.pdf (2012) BASE Show details 18 Native language detection with ’cheap’ learner corpora Julian Brooke; Graeme Hirst In: http://ftp.cs.toronto.edu/pub/gh/Brooke+Hirst-LRCbook-2013.pdf (2011) BASE Show details 19 Native language detection with ’cheap’ learner corpora Julian Brooke; Graeme Hirst In: http://ftp.cs.toronto.edu/pub/gh/Brooke+Hirst-LCR-2012-OLD.pdf (2011) BASE Show details 20 A Multi-Classifier Based Guideline Sentence Young Ho Lee In: ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/d5/b8/Healthc_Inform_Res_2011_Dec_31_17(4)_224-231.tar.gz (2011) BASE Show details Page: 1 2 3 4 5...32

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