TY - GEN
T1 - Cic-IPN@INLi2018
T2 - 10th Working Notes of FIRE - Forum for Information Retrieval Evaluation, FIRE-WN 2018
AU - Markov, I.
AU - Sidorov, G.
PY - 2018
Y1 - 2018
N2 - © 2018 CEUR-WS. All Rights Reserved.In this paper, we describe the CIC-IPN submissions to the shared task on Indian Native Language Identification (INLI 2018). We use the Support Vector Machines algorithm trained on numerous feature types: word, character, part-of-speech tag, and punctuation mark n-grams, as well as character n-grams from misspelled words and emotion-based features. The features are weighted using log-entropy scheme. Our team achieved 41.8% accuracy on the test set 1 and 34.5% accuracy on the test set 2, ranking 3rd in the official INLI shared task scoring.
AB - © 2018 CEUR-WS. All Rights Reserved.In this paper, we describe the CIC-IPN submissions to the shared task on Indian Native Language Identification (INLI 2018). We use the Support Vector Machines algorithm trained on numerous feature types: word, character, part-of-speech tag, and punctuation mark n-grams, as well as character n-grams from misspelled words and emotion-based features. The features are weighted using log-entropy scheme. Our team achieved 41.8% accuracy on the test set 1 and 34.5% accuracy on the test set 2, ranking 3rd in the official INLI shared task scoring.
UR - https://www.scopus.com/pages/publications/85058662261
UR - https://www.scopus.com/pages/publications/85058662261#tab=citedBy
M3 - Conference contribution
VL - 2266
T3 - CEUR Workshop Proceedings
SP - 82
EP - 88
BT - FIRE-WN 2018 - Working Notes of FIRE 2018 - Forum for Information Retrieval Evaluation
A2 - Rosso, P.
A2 - Mehta, P.
A2 - Majumder, P.
A2 - Mitra, M.
PB - CEUR Workshop Proceedings
Y2 - 6 December 2018 through 9 December 2018
ER -