Grigori SIDOROV PhD, Professor and researcher (Full Professor) Natural Language and Text Processing Laboratory Centro de Investigación en Computación (Center for Computing Research CIC) Instituto Politécnico Nacional (National Polytechnic Institute, IPN), Mexico City, Mexico Regular member of Mexican Academy of Sciences National Researcher of Mexico (SNI), level 3 (highest) Editor-in-Chief of the research journal Computación_y_Sistemas (Scopus, DBLP, index of excellence of Conacyt, etc.) Phone: +(52)-55-57296000 ext. 56518, 56544 Mobile: +(52-1)-55-91887293 email:

Curriculum Vitae

Areas of interest - Downloads - Qualifications - Selected publications

Areas of interest

Text processing techniques and systems, automatic dictionary processing, automatic morphological analysis of different languages, automatic syntactic analysis, anaphora resolution, word sense disambiguation, corpus linguistics, parallel texts, linguistic software development.

Current projects: Linguistic tools; parallel texts; automatic analysis of explanatory dictionaries, sentiment analysis, authorship attribution, syntactic n-grams.

Downloads

• Spanish Emotion Lexicon (SEL)
• English-Spanish dictionary of weighted morphological forms
• Interface for the system for fast search of Maya glyphs based on their visual structural description
• Aligned English-Spanish corpus of literary texts (sentence level, 12 large novels).

License agreement:

1. You can use all these programs freely for academic purposes. No warranty.

2. You should inform us about the usage of the programs, and
3. You should cite the corresponding papers in your publications obtained with the help of these programs.
4. If you plan to use the download in a commercial application, please, contact me.
5. Downloading means that you accept the license. Thank you.

New IDEA: Syntactic n-grams = n-grams constructed by following syntactic trees = using syntax in machine learning.

Spanish Emotion Lexicon (SEL) (zip, text, full text).

SEL contains 2,036 words that are associated with the measure of Probability Factor of Affective use (PFA) with respect to at least one basic emotion: joy, anger, fear, sadness, surprise, and disgust. It was marked manually by 19 annotators (scale: null, low, medium, high) and certain thresholds on agreement were implemented. Example of the results, see the table. It means that, say, for the word abundancia (abundance), 50% of annotators chose “medium” and 50% chose “high” values.

A new measure for each word is proposed: Probability Factor of Affective use (PFA). It is based on the percentages presented in the table. Note that PFA is 1 if 100% of annotators relate it to the “high” value of the association with the emotion, and it is 0 if 100% of annotators relate it to the “null” value. So, intuitively it has very clear meaning: the higher the value of the PFA is, the more probable the association of the word with the emotion is. Example of SEL word list:

Palabra PFA Categoría
abundancia 0.83 Alegría
acabalar 0.396 Alegría
acallar 0.198 Alegría
acatar 0.198 Alegría
acción 0.397 Alegría
aceptable 0.594 Alegría
aceptación 0.696 Alegría
acicate 0.429 Alegría
aclamación 0.799 Alegría
aclamar 0.799 Alegría
acogedor 0.83 Alegría...

The data similar to the data in the table is available as well (see full text o xlsx file).

Paper for citing for Spanish Emotion Lexicon (SEL):
Grigori Sidorov, Sabino Miranda-Jiménez, Francisco Viveros-Jiménez, Alexander Gelbukh, Noé Castro-Sánchez, Francisco Velásquez, Ismael Díaz-Rangel, Sergio Suárez-Guerra, Alejandro Treviño, and Juan Gordon. Empirical Study of Opinion Mining in Spanish Tweets. LNAI 7629-7630, 2012, 14 p.

English-Spanish dictionary of weighted morphological forms. Forms are weighted according to the distributions of corresponding grammar classes in corpora. Unicode. Spanish-English version is available on request. For example:

'cause porque 1.0000000
'til hasta 1.0000000
a un 0.4603677
a una 0.3662918
a unas 0.0734382
a uno 0.0031157
a unos 0.0967866
abaci ábaco 0.0561639
abaci ábacos 0.9438361
abacus ábaco 0.9890721
abacus ábacos 0.0109279
abacuses ábaco 0.0561639
abacuses ábacos 0.9438361
abandon abandonábamos 0.0024804
abandon abandonáis 0.0005694
abandon abandonáramos 0.0004860
abandon abandonáremos 0.00071134
abandon abandonásemos 0.0004860...
...abandon abandonaba 0.0779384
abandon abandonabais 0.0000805
abandon abandonaban 0.0226584...

Paper for citing for English-Spanish dictionary of weighted morphological forms:
Grigori Sidorov, Alberto Barrón-Cedeño and Paolo Rosso. English-Spanish Large Statistical Dictionary of Inflectional Forms. In: Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA), 2010, pp. 277-281.

Interface for the system for fast search of Maya glyphs based on their visual structural description (ZIP) or Compressed as EXE file.

Beta-version. The system uses the dictionary of J. Montgomery.
EXE: Download the Glyphs.exe file, execute it, the files will be copied to the folder you choose. Then execute the file SETUP.EXE.
ZIP: Download the Glyphs.zip file, unzip files to the folder you choose . Then execute the file SETUP.EXE.

Papers for citing for glyph search system:
1. Obdulia Pichardo Lagunas, Grigori Sidorov. Diccionario de los glifos maya con descripción visual estructural. In: Proc. of International Conference EURALEX-2008, Barcelona, Spain, July 2008, pp 747–751.
2. Grigori Sidorov, Obdulia Pichardo-Lagunas, and Liliana Chanona-Hernandez. Search Interface to a Mayan Glyph Database based on Visual Characteristics. LNCS 5723, 2009, pp. 222–229.

System for automatic morphological analysis of Spanish (2000-2006) A complete wordlist (beta-version) generated with this system is available.
System for automatic morphological analysis of Russian (1992-2000)

These are EXE files for Windows; DLLs are available on request.
These are the programs that perform lemmatization and provide grammar information of each word form of Spanish or Russian correspondingly.
See detailed description on the corresponding pages – follow the links.

Paper for citing for morphological analysis systems:
A. Gelbukh, G. Sidorov. Approach to construction of automatic morphological analysis systems for inflective languages with little effort. LNCS 2588, 2003, pp. 215–220.

Qualifications

• “Lomonosov” Moscow National University, 1996
  Candidate of Philological sciences (Ph.D.) (Structural, applied and mathematical linguistics)
  Thesis: “Design and implementation of linguistic models, algorithms, and data for the systems with morphological analysis and generation for Russian language”
• “Lomonosov” Moscow National University, 1983-1988
  (M.C. & B.C.) Philological Faculty, Department of Structural and Applied Linguistics.al

Selected publications (author versions)

More than 170 scientific publications. More than 300 references to my works (without self-citing), h-index 11.

1. Gelbukh, G. Sidorov, A. Guzman-Arenas. Use of a weighted topic hierarchy for text retrieval and classification. LNAI 1692, 1999, pp. 130–135.
2. Gelbukh, G. Sidorov, and A. Guzmán-Arenas. A Method of Describing Document Contents through Topic Selection. Proc. SPIRE’99, International Symposium on String Processing and Information Retrieval, Cancun, Mexico, September 22 – 24. IEEE Computer Society Press, 1999, pp. 73-80.
3. Alexander F. Gelbukh and Grigori Sidorov. On Indirect Anaphora Resolution. Proc. PACLING-99, Pacific Association for Computational Linguistics, ISBN 0-9685753-0-7, University of Waterloo, Waterloo, Ontario, Canada, August 25-28, 1999, pp. 181-190.
4. Grigori Sidorov, Alexander Gelbukh. Demonstrative pronouns as markers of indirect anaphora. In: Proc. 2nd International Conference on Cognitive Science and 16th Annual Meeting of the Japanese Cognitive Science Society Joint Conference (ICCS/JCSS99), July 27-30, 1999, Tokyo, Japan, pp. 418-423.
5. Alexander Gelbukh and Grigori Sidorov. Approach to construction of automatic morphological analysis systems for inflective languages with little effort. LNCS 2588, 2003, pp. 215–220.
6. Alexander Gelbukh, Grigori Sidorov, and Liliana Chanona-Hernández. Compilation of a Spanish representative corpus. LNCS 2276, 2002, pp. 285–288.
7. Alexander Gelbukh and Grigori Sidorov. Automatic Selection of Defining Vocabulary in an Explanatory Dictionary. LNCS 2276, 2002, pp. 300–303.
8. Alexander Gelbukh, Grigori Sidorov, San-Yong Han, and Erika Hernández-Rubio. Automatic Enrichment of Very Large Dictionary of Word Combinations on the Basis of Dependency Formalism. LNAI 2972, 2004, pp 430-437.  //(discussion of collocation concept)
9. Alexander Gelbukh and Grigori Sidorov. Alignment of Paragraphs in Bilingual Texts using Bilingual Dictionaries and Dynamic Programming. LNCS 4225, 2006, pp 824-833.
10. Gaspár Ramírez, James L. Fidelholtz, Héctor Jiménez, Grigori Sidorov. Elaboración de un diccionario de verbos del español a partir de una lexicografía sistemática. In: “Avances en la Ciencia de la computación”, Proc. of 7 Int .Conf. ENC-2006, San Luís Potosi, México, 2006, pp.270-275.
11. Alexander Gelbukh, Grigori Sidorov, SangYong Han. On Some Optimization Heuristics for Lesk-Like WSD Algorithms. LNCS 3513, 2005, pp. 402–405.
12. Alexander Gelbukh and Grigori Sidorov. Zipf and Heaps Laws’ Coefficients Depend on Language. LNCS 2004, 2001, pp. 330–333.

13.  Grigori Sidorov, Obdulia Pichardo-Lagunas, and Liliana Chanona-Hernandez. Search Interface to a Mayan Glyph Database based on Visual Characteristics. LNCS 5723, 2009, pp. 222–229.

14. Castro-Sánchez, N. A., Sidorov, G. Automatic Acquisition of Synonyms of Verbs from an Explanatory Dictionary using Hyponym and Hyperonym Relations. LNCS 6718, 2011.
15. María de los Ángeles Alonso-Lavernia, Argelio Víctor De-la-Cruz-Rivera, and Grigori Sidorov. Generation of Natural Language Explanations of Rules in an Expert System. LNCS 3878, 2006, pp. 311-314.
16. Grigori Sidorov, Sabino Miranda-Jiménez, Francisco Viveros-Jiménez, Alexander Gelbukh, Noé Castro-Sánchez, Francisco Velásquez, Ismael Díaz-Rangel, Sergio Suárez-Guerra, Alejandro Treviño, and Juan Gordon. Empirical Study of Machine Learning Based Approach for Opinion Mining in Tweets. LNAI 7629, 2012, pp. 1-14 (available on the web since Sep-10-2012).
17. Grigori Sidorov, Francisco Velasquez, Efstathios Stamatatos, Alexander Gelbukh, and Liliana Chanona-Hernández. Syntactic Dependency-based N-grams as Classification Features. LNAI 7630, 2012, pp. 1-11 (available on the web since Sep-10-2012).

You can find more information about the papers and about our laboratory on the page of Alexander Gelbukh. More information about the annual International Conference on computational linguistics CICLing (Springer, LNCS series) or about Mexican International Conference on Artificial Intelligence MICAI (Springer, LNAI series) .

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