Grigori Sidorov – författare

In this book, we propose and systematize the concept of syntactic n-grams, which allows using syntactic information within the automatic text processing methods related to classification or clustering. It is a very interesting example of application of linguistic information in the automatic (computational) methods. Roughly speaking, the suggestion is to follow syntactic trees and construct n-grams based on paths in these trees. There are several types of non-linear n-grams; future work should determine, which types of n-grams are more useful in which natural language processing (NLP) tasks.

This book is intended for specialists in the field of computational linguistics. However, we made an effort to explain ina clear manner how to use n-grams; we provide a large number of examples, and therefore we believe that the book is also useful for graduate students who already have some previous background in the field.

The total of 58 papers presented in these two volumes was carefully reviewed and selected from  129 submissions.

The first volume, Advances in Computational Intelligence, contains 30 papers structured

into three sections:

– Machine and Deep Learning

– Evolutionary and Metaheuristic Algorithms

The second volume, Advances in Soft Computing, contains 28 papers structured into two sections:

– Natural Language Processing

– Intelligent Applications and Robotics

The total of 58 papers presented in these two volumes was carefully reviewed and selected from  129 submissions.

The first volume, Advances in Computational Intelligence, contains 30 papers structured

into three sections:

– Machine and Deep Learning

– Evolutionary and Metaheuristic Algorithms

The second volume, Advances in Soft Computing, contains 28 papers structured into two sections:

– Natural Language Processing

– Intelligent Applications and Robotics

The two volume set LNAI 9413 + LNAI 9414 constitutes theproceedings of the 14th Mexican International Conference on ArtificialIntelligence, MICAI 2015, held in Cuernavaca, Morelos, Mexico, in October 2015.

The total of 98 papers presented in these proceedings wascarefully reviewed and selected from 297 submissions. They were organized intopical sections named: natural language processing; logic and multi-agentsystems; bioinspired algorithms; neural networks; evolutionary algorithms;fuzzy logic; machine learning and data mining; natural language processingapplications; educational applications; biomedical applications; imageprocessing and computer vision; search and optimization; forecasting; andintelligent applications.

The two-volume set LNAI 10061 and 10062 constitutes the proceedings of the 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, held in Cancún, Mexico, in October 2016.  The total of 86 papers presented in these two volumes was carefully reviewed and selected from 238 submissions. The contributions were organized in the following topical sections:  Part I: natural language processing; social networks and opinion mining; fuzzy logic; time series analysis and forecasting; planning and scheduling; image processing and computer vision; robotics. Part II: general; reasoning and multi-agent systems; neural networks and deep learning; evolutionary algorithms; machine learning; classification and clustering; optimization; data mining; graph-based algorithms; and intelligent learning environments.