Massimiliano Ciaramita

Papers


2014
  • A scalable Gibbs sampler for probabilistic entity linking. N. Houlsby and M. Ciaramita. ECIR. Amsterdam. (PDF)

2013
  • A framework for benchmarking entity-annotation systems. M. Cornolti, P. Ferragina and M. Ciaramita. ACM WWW, Rio de Janeiro. (PDF)
  • Scalable probabilistic entity-topic modeling. N. Houlsby and M. Ciaramita. arXiv preprint arXiv:1309.0337.

2012
  • Topical clustering of search results. U. Scaiella, P. Ferragina, A. Marino and M. Ciaramita. ACM WSDM. Seattle. (PDF). 

2011
  • Learning to Rank Answers to Non-Factoid Questions from Web Collections. M. Surdeanu, M. Ciaramita and H. Zaragoza. Computational Linguistics. 37(2). (PDF).
  • Piggyback: Using Search Engines for Robust Cross-Domain Named Entity Recognition. S. Rued, M. Ciaramita, J. Mueller and H. Schuetze. ACL-HLT 2011. Portland. (PDF). Web appendix, including data, statistics etc.
  • Dependency parsing with second-order feature maps and annotated semantic information. M. Ciaramita, G. Attardi. In H. Bunt, P. Merlo and J. Nivre (eds.), Trends in Parsing Technology. Text, Speech and Language Technology Series, Vol 43, pp.87-104. Springer. 2011. (PDF)

2010
  • Generalized syntactic and semantic models of query reformulation. A. Herdagdelen, M. Ciaramita, D. Mahler, M. Holmqvist, K. Hall, S. Riezler and E. Alfonseca. 33rd ACM SIGIR Conference, Geneva, Switzerland. (PDF)
  • Learning Dense Models of Query Similarity from User Click Logs. F. DeBona, S. Riezler, K. Hall, M. Ciaramita, A. Herdagdelen and M. Holmqvist. 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2010), Los Angeles. (PDF)
  • Adaptive parameters for entity recognition with perceptron HMMs. M. Ciaramita and O. Chapelle. ACL 2010 Workshop on Domain Adaptation for Natural Language Processing (DANLP), Uppsala, Sweden. (PDF)
  • Instance Sense Induction from Attribute Sets. R. Martin-Brualla, E. Alfonseca, M. Pasca, K. Hall, E. Robledo-Arnuncio and M. Ciaramita. 23rd Coling, Beijing, China. (PDF).

2009
  • Gazpacho and summer rash: Lexical relationships from temporal patterns of web search queries. E. Alfonseca, M. Ciaramita and K. Hall. Empirical Methods in Natural Language Processing (EMNLP), Singapore. (PDF)
  • The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages. J. Hajič, M. Ciaramita, R. Johansson, D. Kawahara, M.A. Martí, L. Màrquez, A. Meyers, J. Nivre, S. Padó, J. Štěpánek, P. Straňák, M.Surdeanu, N. Xue and Y. Zhang. In Proceedings of the 13th Conference on Computational Natural Language Learning (CoNLL-2009), Boulder, CO, USA. (PDF)
  • Company-oriented extractive summarization of financial news. K. Filippova, M. Surdeanu, M. Ciaramita, H. Zaragoza. European chapter of the Association for Computational Linguistics (EACL), Athens, Greece. (PDF)

2008
  • To swing or not to swing: Learning when (not) to advertise. A. Broder, M. Ciaramita, M. Fontoura, E. Gabrilovich, V. Josifovski, D. Metzler, V. Murdock, V. Plachouras. ACM Conference on Information and Knowledge Management (CIKM), Napa Valley, USA. (PDF)
  • Boosting image retrieval through aggregating search results based on visual annotations. X. Olivares, M. Ciaramita, and R. van Zwol. ACM Conference on Multimedia (MM), Vancouver, Canada. (PDF)
  • Learning to tag and tagging to learn: A case study on Wikipedia. P. Mika, M. Ciaramita, H. Zaragoza, J. Atserias. IEEE Intelligent Systems. 23(5), pp.26-33. 2008. (PDF)
  • Towards semantic search. R. Baeza-Yates, M. Ciaramita, P. Mika, H. Zaragoza. NLDB, LNCS 5039, pp.4-11. 2008. (PDF)
  • Learning to rank answers on large online QA collections. M. Surdeanu, M. Ciaramita, H. Zaragoza. Association for Computational Linguistics (ACL-HLT). 2008. (PDF)
  • Online learning from click data for sponsored search. M. Ciaramita, V. Murdock, V. Plachouras. World Wide Web Conference (WWW). 2008. (PDF)
  • DeSRL: A linear-time semantic role labeling system. M. Ciaramita, G. Attardi, F. Dell'Orletta, M. Surdeanu. Conference on Natural Language Learning Shared Task (CoNLL). 2008. (PDF)
  • Semantically annotated snapshot of the English Wikipedia. J. Atserias, H. Zaragoza, M. Ciaramita, G. Attardi. Sixth International Language Resources and Evaluation (LREC). 2008. (PDF)
  • Semantic associations for contextual advertising. M. Ciaramita, V. Murdock, V. Plachouras. Journal of Electronic Commerce Research. 9(1), pp-1-15. 2008. (PDF).
  • Unsupervised learning of semantic relations for molecular biology ontologies. M. Ciaramita, A. Gangemi, E. Ratsch, J. Saric, I. Rojas. In P. Buitelaar and P. Cimiano (eds.), Bridging the Gap between Text and Knowledge: Selected Contributions to Ontology Learning and Population from Text, Frontiers in Artificial Intelligence and Applications Series, IOS Press. 2008. (PDF)
2007
  • Tree revision learning for dependency parsing. G. Attardi, M. Ciaramita. Human Language Technology and North American chapter of the Assocation for Computational Linguistics (HLT-NAACL). 2007. (PDF)
  • Dependency parsing with second-order feature maps and annotated semantic information. M. Ciaramita, G. Attardi. 10th International Conference on Parsing Technology (IWPT). 2007. (PDF)
  • A noisy channel approach to contextual advertising. V. Murdock, M. Ciaramita, V. Plachouras. Data Mining and Audience Intelligence for Advertising Workshop (ADKDD). 2007. (PDF)
  • Ranking very many typed entities in Wikipedia. H. Zaragoza, H. Rode, P. Mika, J. Atserias, M. Ciaramita, G. Attardi.16th ACM International Conference on Information and Knowledge Management (CIKM). 2007. (PDF)
  • Semantic domains and supersense tagging for domain-specific ontology learning. D. Picca, A. Gliozzo, M. Ciaramita. RIAO. 2007. (PDF)
  • Multilanguage dependency parsing and domain adaptation using DeSR. G. Attardi, F. Dell’Orletta, M. Simi, A. Chanev, M. Ciaramita. CoNLL Shared Task Session of EMNLP-CoNLL. 2007. (PDF)
  • Robust information extraction with perceptrons. M. Surdeanu, M. Ciaramita. NIST Automatic Content Extraction Workshop (ACE). 2007. (PDF)
  • SuperSenseLearner: Combining SenseLearner with supersense and other coarse semantic features. R. Mihalcea, A. Csomai, M. Ciaramita. 4th International Workshop on Semantic Evaluations (SemEval/ACL). 2007. (PDF)
  • PoS tagging with a named entity tagger. M. Ciaramita, J. Atserias. Intelligenza Artificiale, 4 (2), pp. 28-29. 2007. (PDF)
  • Named entity tagging with a PoS tagger. M. Ciaramita, J. Atserias. Intelligenza Artificiale, 4 (2), pp. 79-80. 2007. (PDF)
  • World knowledge in broad-coverage information filtering. B. Hagedorn, M. Ciaramita, J. Atserias. ACM Conference on Research and Development in Information Retrieval (SIGIR, Poster). 2007. (PDF)
2006
  • Measuring Web-corpus randomness: A progress report. M. Ciaramita, M. Baroni. In Marco Baroni and Silvia Bernardini (eds.), Wacky! Working papers on the Web as Corpus, Bologna: Gedit. 127-158. 2006. (PDF)
  • A figure of merit for the evaluation of Web-corpus randomness. M. Ciaramita, M. Baroni. European chapter of the Association for Computational Linguistics (EACL). 2006. (PDF)
  • Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger. M. Ciaramita, Y. Altun. Empirical Methods in Natural Language Processing (EMNLP). 2006. (PDF)
  • Modelling ontology evaluation and validation. A. Gangemi, C. Catenacci, M. Ciaramita, J. Lehman. 3rd European Semantic Web Conference (ESWC). 2006. (PDF)
  • Qood grid: A metaontology-based framework for ontology evaluation and selection. A. Gangemi, C. Catenacci, M. Ciaramita, J. Lehmann. Evaluation of Ontologies for the Web Workshop (EON/WWW). 2006. (PDF)
2005
  • Apprendimento automatico di ontologie da testi: Selezione di relazioni semantiche da un corpus di biologia molecolare. M. Ciaramita. In S. Bassi (ed.), Seminari Signum 2005, Edizioni della Normale. Pisa. 2008.
  • A theoretical framework for ontology evaluation and validation. A. Gangemi, C. Catenacci, M. Ciaramita and J. Lehmann. Semantic Web Applications and Perspectives (SWAP) - 2nd Italian Semantic Web Workshop.
  • Hierarchical preferences in a broad-coverage lexical taxonomy. M. Ciaramita, S. Sloman, M. Johnson, E. Upfal. XXVII Annual Conference of the Cognitive Science Society (CogSci). 2005. (PDF)
  • Unsupervised learning of semantic relations between concepts of a molecular biology ontology. M. Ciaramita, A. Gangemi, E. Ratsch, J. Saric, I. Rojas. 19th International Joint Conference on Artificial Intel ligence (IJCAI). 2005. (PDF)
  • Named-entity recognition in novel domains with external lexical knowledge. M. Ciaramita, Y. Altun. Advances in Structured Learning for Text and Speech Processing Workshop (NIPS). 2005. (PDF)
2004
  • Broad-coverage hierarchical word sense disambiguation. M. Ciaramita. Ph.D. Thesis. Department of Cognitive and Linguistic Sciences, Brown University. 2004. (PDF)
  • Multi-component word sense disambiguation. M. Ciaramita, M.Johnson. Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text (Senseval 3/ACL). 2004. (PDF)
2003
  • Supersense tagging of unknown nouns in WordNet. M. Ciaramita, M. Johnson. Empirical Methods in Natural Language Processing (EMNLP). 2003. (PDF)
  • Hierarchical semantic classification: Word sense disambiguation with world knowledge. M. Ciaramita, T. Hofmann, M. Johnson. 18th International Joint Conference on Artificial Intelligence (IJCAI). 2003. (PDF)
  • Learning with taxonomies: Classifying documents and words. T. Hofmann, L. Cai, M. Ciaramita. Syntax Semantics and Statistics
    Workshop (NIPS). 2003. (PDF)
2002
  • Boosting automatic lexical acquisition with morphological information. M. Ciaramita. Workshop on Unsupervised Lexical Acquisition (SIGLEX/ACL). 2002. (PDF
2000
  •  Explaining away ambiguity: Learning verb selectional preference with Bayesian networks. M. Ciaramita, M. Johnson. 18th International Conference on Computational Linguistics (COLING). 2000. (PDF, extended version)

Software

  • Supersense tagger: (with Yasemin Altun and Jordi Atserias) an implementation of Michael Collins perceptron HMM for broad sense disambiguation (Wordnet supersenses), PoS tagging and named entity recognition.
  • DeSR: (contributor) Giuseppe Attardi's transition-based multilingual dependency parser.

Data

Prototypes

  • Correlator: a prototype built at the Yahoo! Research Barcelona lab to explore new ways of information browsing based on NLP pre-processing and specialized ranking methods.
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