Papers by Alexander Gelbukh
Cicling, 2004
Ce numéro publie les actes de la seconde conférence annuelle consacrée à la linguistique informat... more Ce numéro publie les actes de la seconde conférence annuelle consacrée à la linguistique informatique et au traitement intelligent des textes, CICLing 2001(Mexico, 18-24 Février 2001). Les interventions en linguistique informatique ont porté sur les thèmes suivants: théories et formalismes, sémantique, anaphore et référence, désambiguïsation, traduction, génération de texte, dictionnaires et corpus, morphologie, techniques d'analyse syntaxique automatique. Dans le domaine du traitement intelligent des textes, les communications se ...
Ce numéro publie les actes de la seconde conférence annuelle consacrée à la linguistique informat... more Ce numéro publie les actes de la seconde conférence annuelle consacrée à la linguistique informatique et au traitement intelligent des textes, CICLing 2001(Mexico, 18-24 Février 2001). Les interventions en linguistique informatique ont porté sur les thèmes suivants: théories et formalismes, sémantique, anaphore et référence, désambiguïsation, traduction, génération de texte, dictionnaires et corpus, morphologie, techniques d'analyse syntaxique automatique. Dans le domaine du traitement intelligent des textes, les communications se ...
Lecture Notes in Computer Science, 2010
Page 1. Computing Transfer Score in Example-Based Machine Translation Rafał Jaworski Adam Mickiew... more Page 1. Computing Transfer Score in Example-Based Machine Translation Rafał Jaworski Adam Mickiewicz University Poznań, Poland rjawor@amu.edu.pl Abstract. This paper presents an idea in Example-Based Machine ...
Computacion Y Sistemas, Mar 1, 2008
Descripción: ONE OF THE PROBLEMS OF INFORMATION RETRIEVAL IN INTERNET AND DIGITAL LIBRARIES IS LO... more Descripción: ONE OF THE PROBLEMS OF INFORMATION RETRIEVAL IN INTERNET AND DIGITAL LIBRARIES IS LOW PRECISION: A HIGH NUMBER OF RETRIEVED DOCUMENTS OF LOW RELEVANCE. FOR EXAMPLE, A PERSON LOOKS FOR INFORMATION ABOUT JAGUARS (THE ANIMAL) AND THE DOCUMENTS RETRIEVED ARE ABOUT THE MODEL OF A CAR. THIS PROBLEM ARISES DUE TO AMBIGUITY OF DIFFERENT SENSES OF WORDS. THE TASK OF DETERMINING THE CORRECT INTERPRETATION OF A WORD ...
This book constitutes the refereed proceedings of the 5th Mexican International Conference on Art... more This book constitutes the refereed proceedings of the 5th Mexican International Conference on Artificial Intelligence, MICAI 2006, held in Apizaco, Mexico in November 2006. It contains over 120 papers that address such topics as knowledge representation and reasoning, machine learning and feature selection, knowledge discovery, computer vision, image processing and image retrieval, robotics, as well as bioinformatics and medical applications.
Research in Computing Science, 2013
Lingvisticae Investigationes, 2007
Abstract: We present a linguistic analysis of Named Entities in Spanish texts. Our work is focuse... more Abstract: We present a linguistic analysis of Named Entities in Spanish texts. Our work is focused on the determination of the structure of complex proper names: names with coordinated constituents, names with prepositional phrases and names formed by several content words initialized by a capital letter. We present the analysis of circa 49,000 examples obtained from Mexican newspapers. We detailed their structure and give some notions about the context surrounding them. Since named entities belong to open class of ...
Cicling, 2009
This book constitutes the proceedings of the 11th International Conference on Computational Lingu... more This book constitutes the proceedings of the 11th International Conference on Computational Linguistics and Intelligent Text Processing, held in Iaşi, Romania, in March 2010. The 60 paper included in the volume were carefully reviewed and selected from numerous submissions. The book also includes 3 invited papers. The topics covered are: lexical resources, syntax and parsing, word sense disambiguation and named entity recognition, semantics and dialog, humor and emotions, machine translation and ...
ABSTRACT The article presents the experiments carried out as part of the participation in the mai... more ABSTRACT The article presents the experiments carried out as part of the participation in the main task (English dataset) of QA4MRE@CLEF 2013. In the developed system, we first combine the question Q and each candidate answer option A to form (Q , A) pair. Each pair has been considered a Hypothesis (H). We have used Morphological Expansion to rebuild the H. Then, each H has been verified by assigning a matching score. Stop words and interrogative words are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document using Lucene. Relevant sentences are retrieved from the associated document based on the TF-IDF of the matching query words along with n-gram overlap of the sentence with the H. Each retrieved sentence defines the Text T. Each T-H pair is assigned a ranking score that works on textual entailment principle. The inference weight i.e., matching score has automatically been assigned to each answer options based on their inference matching. Each sentence in the associated document has contributed an inference score to each H. The candidate answer option that receives the highest inference score has been identified as the most relevant option and selected as the answer to the given question.
ABSTRACT The article presents the experiments carried out as part of the participation in the pil... more ABSTRACT The article presents the experiments carried out as part of the participation in the pilot task of QA4MRE@CLEF 2013. In the developed system, we have first generated answer pattern by combining the question and each answer option to form the Hypothesis (H). Stop words and interrogative word are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document using Lucene. Relevant sentences are retrieved from the associated document based on the TF-IDF of the matching query words along with n-gram overlap of the sentence with the H. Each retrieved sentence defines the Text T. Each T-H pair is assigned a ranking score that works on textual entailment principle. A matching score is automatically assigned to each answer options based on the matching. A parallel procedure also generates the possible answer patterns from given questions and answer options. Each sentence in the associated document is assigned an inference score with respect to each answer pattern. Evaluated inference score for each answer option is added with the matching score. The answer option that receives the highest selection score is identified as the most relevant option and selected as the answer to the given question.
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Papers by Alexander Gelbukh