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Displaying 1-11 out of 11 total
Comparing Commercial Tools and State-of-the-Art Methods for Generating Text Summaries
Found in: Mexican International Conference on Artificial Intelligence
By René Arnulfo García-Hernández, Yulia Ledeneva, Griselda Matías Mendoza, Ángel Hernández Dominguez, Jorge Chavez, Alexander Gelbukh, José Luis Tapia Fabela
Issue Date:November 2009
pp. 92-96
Nowadays, there are commercial tools that allow automatic generation of text summaries. However, it is not known the quality of the generated summaries and the method that it is used for the generation of the summaries using these commercial tools. This pa...
 
Natural Language Processing
Found in: Hybrid Intelligent Systems, International Conference on
By Alexander Gelbukh
Issue Date:December 2005
pp. 6
Natural Language Processing (NLP) is a major area of artificial intelligence research, which in its turn serves as a field of application and interaction of a number of other traditional AI areas. Until recently, the focus in AI applications in NLP was on ...
   
Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining
Found in: IEEE Intelligent Systems
By Soujanya Poria,Alexander Gelbukh,Amir Hussain,Newton Howard,Dipankar Das,Sivaji Bandyopadhyay
Issue Date:March 2013
pp. 31-38
SenticNet 1.0 is one of the most widely used, publicly available resources for concept-based opinion mining. The presented methodology enriches SenticNet concepts with affective information by assigning an emotion label.
 
Enriching SenticNet Polarity Scores through Semi-Supervised Fuzzy Clustering
Found in: 2012 IEEE 12th International Conference on Data Mining Workshops
By Soujanya Poria,Alexander Gelbukh,Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay
Issue Date:December 2012
pp. 709-716
SenticNet 1.0 is one of the most widely used freely-available resources for concept-level opinion mining, containing about 5,700 common sense concepts and their corresponding polarity scores. Specific affective information associated to such concepts, howe...
 
Dependency Parser Based Textual Entailment System
Found in: Artificial Intelligence and Computational Intelligence, International Conference on
By Partha Pakray, Sivaji Bandyopadhyay, Alexander Gelbukh
Issue Date:October 2010
pp. 393-397
The development of a parser based textual entailment system that is based on comparing the dependency relations in both the text and the hypothesis has been reported. The textual entailment system uses the CCG Parser and the Stanford Parser. The Dependency...
 
Elitistic Evolution: A Novel Micro-population Approach for Global Optimization Problems
Found in: Mexican International Conference on Artificial Intelligence
By Francisco Viveros-Jiménez, Efren Mezura-Montes, Alexander Gelbukh
Issue Date:November 2009
pp. 15-20
Micro-population Evolutionary Algorithms (μ-EAs) are useful tools for optimization purposes. They can be used as optimizers for unconstrained, constraint and multi-objective problems. μ-EAs distinctive feature is the usage of very small populations. A nove...
 
Web-Based Variant of the Lesk Approach to Word Sense Disambiguation
Found in: Mexican International Conference on Artificial Intelligence
By Miguel Ángel Ríos Gaona, Alexander Gelbukh, Sivaji Bandyopadhyay
Issue Date:November 2009
pp. 103-107
Word Sense Disambiguation (WSD) is the task of selecting the meaning of a word based on the context in which the word occurs. The principal statistical WSD approaches are supervised and unsupervised learning. The Lesk method is an example of unsupervised d...
 
Customization of Natural Language Interfaces to Databases: Beyond Domain Portability
Found in: Mexican International Conference on Computer Science
By José Antonio Zárate Marceleño, Rodolfo A. Pazos R., Alexander Gelbukh
Issue Date:September 2009
pp. 373-378
The first Natural Language Interfaces to Databases were built and designed for specific domains, and their customization processes implied source code manipulation. Open systems and database inter-operability enabled these interfaces to be independent of t...
 
Performance of Inductive Method of Model Self-Organization with Incomplete Model and Noisy Data
Found in: Mexican International Conference on Artificial Intelligence
By Natalia Ponomareva, Mikhail Alexandrov, Alexander Gelbukh
Issue Date:October 2008
pp. 101-108
Inductive method of model self-organization (IMMSO) developed in 80s by A. Ivakhnenko is an evolutionary machine learning algorithm, which allows selecting a model of optimal complexity that describes or explains a limited number of observation data when a...
 
Evaluation of TnT Tagger for Spanish
Found in: Mexican International Conference on Computer Science
By Raúl Morales Carrasco, Alexander Gelbukh
Issue Date:September 2003
pp. 18
Part of Speech (POS) tagger is a necessary module in many natural language text processing tasks. A POS tagger is a program that accepts an unprepared raw text in input and to each word adds a tag specifying its grammatical properties, such as part of spee...
 
A Method of Describing Document Contents through Topic Selection
Found in: String Processing and Information Retrieval, International Symposium on
By Alexander Gelbukh, Grigori Sidorov, Adolfo Guzmán-Arenas
Issue Date:September 1999
pp. 73
Given a large hierarchical dictionary of concepts, the task of selection of the concepts that describe the contents of a given document is considered. The problem consists in proper handling of the top-level concepts in the hierarchy. As a representation o...
 
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