Home   >   CSC-OpenAccess Library   >   Theory & Algorithms   >  International Journal of Computational Linguistics (IJCL)
International Journal of Computational Linguistics (IJCL)
An International peer-review journal operated under CSC-OpenAccess Policy.
ISSN - 2180-1266
Published - Bi-Monthly   |   Established - 2010   |   Year of Publication - 2023

SUBMISSION
February 28, 2023

NOTIFICATION
March 31, 2023

PUBLICATION
April 30, 2023

 
         
HOME   About IJCL   Editorial Board   Call For Papers/Editors   Submission Guidelines   Citation Report   Issues Archive   Subscribe IJCL
VIDEO PRESENTATIONS
Visit Video Section to see author video presentations on their publications.
 
 
RESEARCH CENTERS, INSTITUTES & UNIVERSITIES
 
SEE COMPLETE LIST OF PUBLICATIONS
 

IJCL CITATION IMPACT
1.517

Refer to In-Process Citation Report for IJCL for complete details.
 
LIST OF JOURNALS
Complete list of Open Access journals with free access its publications.
 
For Inquiries & Fast Response cscpress@cscjournals.org

CITATION REPORT FOR IJCL

Below calculations are based on citations that are extracted through Google Scholar until December 31, 2020.


Total Citations = 91
Self Citations = 0
Total Publications = 60


Citation Impact
(Total Citations - Self Citations) / Total Publications

Citation Impact
(91 - 0) / 60 = 1.517

 
SR
M-CODE
CITATION
1
NAKAJIMA, Y., PTASZYNSKI, M., HONMA, H., & MASUI, F. (2016). An Extraction Method for Future Reference Expressions Using Morphological and Semantic Patterns.
2
Haroon, R. P., & Shaharban, T. A. Malayalam machine translation using hybrid approach.
3
Dzulkifli, M. A., bin Abdul Rahman, A. W., Badi, J. A. B., & Solihu, A. K. H. (2016). Routes to Remembering: Lessons from al Huffaz. Mediterranean Journal of Social Sciences, 7(3 S1), 121.
4
Wegari, G. M., Melucci, M., & Teferra, S. (2015, September). Suffix sequences based morphological segmentation for Afaan Oromo. In AFRICON, 2015 (pp. 1-6). IEEE.
5
Siddiqui, M. A., Dahab, M. Y., & Batarfi, O. A. (2015). Building A Sentiment Analysis Corpus With Multifaceted Hierarchical Annotation.
6
Badaro, G., Baly, R., Akel, R., Fayad, L., Khairallah, J., Hajj, H., ... & Shaban, K. B. (2015, July). A Light Lexicon-based Mobile Application for Sentiment Mining of Arabic Tweets. In ANLP Workshop 2015 (p. 18).
7
Duwairi, R. M., Ahmed, N. A., & Al-Rifai, S. Y. Detecting sentiment embedded in Arabic social media–A lexicon-based approach. Journal of Intelligent and Fuzzy Systems.
8
Siddiqui, M. A., Dahab, M. Y., & Batarfi, O. A. (2015). Building A Sentiment Analysis Corpus With Multifaceted Hierarchical Annotation.
9
Ali, M. N. Y., Sorwar, G., Toru, A., Islam, M. A., & Shamsujjoha, M. (2015). Morphological Rules of Bangla Repetitive Words for UNL Based Machine Translation. In Advances in Swarm and Computational Intelligence (pp. 401-408). Springer International Publishing.
10
Negesse, F. (2015). Classification of Oromo Dialects: A Computational Approach.
11
Afzal, N., & Bawakid, A. (2015). Comparison between Surface-based and Dependency-based Relation Extraction Approaches for Automatic Generation of Multiple-Choice Questions.
12
Eskander, R., & Rambow, O. SLSA: A Sentiment Lexicon for Standard Arabic.
13
Alotaibi, S. S. (2015). Sentiment Analysis in the Arabic Language Using Machine Learning (Doctoral dissertation, Colorado State University. Libraries).
14
Alcalde, J. (2015). Linguistic justice: an interdisciplinary overview of the literature.
15
Saha, A. K., Mridha, M., Hussein, M. R., & Das, J. K. (2015, June). Design and implementation of an efficient DeConverter for generating Bangla sentences from UNL expression. In Informatics, Electronics & Vision (ICIEV), 2015 International Conference on (pp. 1-6). IEEE.
16
Nijim, A., El Shenawy, A., Mostafa, M. T., & Alez, R. A. Anovel Approach for recognizing text in arabic ancient manuscripts.
17
Al-Bakry, A. M., & Al-Rikaby, M. K. Enhanced Levenshtein Edit Distance Method functioning as a String-to-String Similarity Measure. Distributed Agents for Web Content Filtering, 48.
18
Alrabiah, M., Al-salman, A., & Atwell, E. A New Distributional Semantic Model for Classical Arabic.
19
Thapar, P. (2014). A Hybrid Approach used to Stem Punjabi Words.
20
Godase, A., & Govilkar, S. machine translation development for indian languages and its approaches.
21
Seedah, D. P. K. (2014). Retrieving information from heterogeneous freight data sources to answer natural language queries (Doctoral dissertation).
22
Shirvi, N. N., & Panchal, M. H. (2014). Translation of English Algorithm in C Program using Syntax Directed Translation Schema.
23
Larcom, M. K. (2014). The Minimalist Machine: An Implementation of Arabic Structures and Syntax.
24
Badaro, G., Baly, R., Hajj, H., Habash, N., & El-Hajj, W. (2014). A large scale Arabic sentiment lexicon for Arabic opinion mining. ANLP 2014, 165.
25
Bayoudhi, A., Koubaa, H., Belguith, L. H., & Ghorbel, H. Vers un lexique arabe pour l’analyse des opinions et des sentiments.
26
Alrabiah, M., Al-Salman, A., & Atwell, E. (2014, October). The refined MI: A significant improvement to mutual information. In Asian Language Processing (IALP), 2014 International Conference on (pp. 132-135). IEEE.
27
Bijimol, T. K., & Abraham, J. T. (2014). A Study of Machine Translation Methods.
28
Atwell, E., & Alfaifi, A. Arabic corpus linguistics research at the University of Leeds.
29
Atwell, E., & Alfaifi, A. Arabic corpus linguistics research at the University of Leeds.
30
Abdalkader, M. (2014). Sentiment Analysis of Egyptian Arabic in Social Media.
31
D'hondt, E. K. L. (2014). Cracking the patent: using phrasal representations to aid patent classfication. [Sl: sn].
32
NAKAJIMA, Y., PTASZYNSKI, M., HONMA, H., & MASUI, F. (2014). FAN-14-029 Extraction of Future Reference Expressions in Trend Information. ? nn te ri ji e nn Suites ? su Te Rousseau · ? nn Polyster ji ? Rousseau Lecture Proceedings, 2014 (24) , 129-134.
33
Ptaszynski, M., Masui, F., Rzepka, R., & Araki, K. (2014). Detecting emotive sentences with pattern-based language modelling. Procedia Computer Science, 35, 484-493.
34
Girma, T., Landage, S. M., Wasif, A. I., Dhuppe, P., Kumar, M., & Sharma, S. (2014). Human language technologies and Affan Oromo. International Journal of Advanced Research in Engineering and Applied Sciences, 3(5), 1-13.
35
Kulkarni, S., & Sagar, B. M. (2014). A Survey on Named Entity Recognition for South Indian Languages.
36
Abbas, Q. (2014, August). Semi-semantic part of speech annotation and evaluation. In Proceedings of ACL 8th Linguistic Annotation Workshop held in conjunction with COLING, Association of Computational Linguistics, P (pp. 75-81).
37
Abbas, Q. (2014). Building Computational Resources: The URDU. KON-TB Treebank and the Urdu Parser (Doctoral dissertation).
38
Abbas, Q. (2014). A Stochastic Prediction Interface for Urdu. International Journal of Intelligent Systems and Applications (IJISA), 7(1), 94.
39
Ptaszynski, M., Masui, F., Rzepka, R., & Araki, K. (2014). Automatic Extraction of Emotive and Non-emotive Sentence Patterns. In Proceedings of The Twentieth Annual Meeting of The Association for Natural Language Processing (NLP2014) (pp. 868-871).
40
Nakajima, Y., Ptaszynski, M., Honma, H., & Masui, F. (2014, March). Investigation of Future Reference Expressions in Trend Information. In Proceedings of the 2014 AAAI Spring Symposium Series (pp. 31-38).
41
Ptaszynski, M., Masui, F., Rzepka, R., & Araki, K. (2014). First Glance on Pattern-based Language Modeling. Language Acquisition and Understanding Research Group (LAU), Technical Reports, Summer.
42
Sakuta, H., & Adachi, E. How Differently Do We Talk? A Study of Sentence Patterns in Groups of Different Age, Gender and Social Status.
43
Hinkova, A., Bubnik, Z., & Kadlec, P. (2014). Chemical Composition of Sugar and Confectionery Products. In Handbook of Food Chemistry (pp. 1-34). Springer Berlin Heidelberg.
44
Seedah, D. P. K. (2014). Retrieving information from heterogeneous freight data sources to answer natural language queries (Doctoral dissertation).
45
Morwal, S., Chopra, D., & Purohit, G. N. named entity recognition in natural languages using transliteration.
46
Jimmy, L., & Kaur, D. (2013). Named entity recognition in Manipuri: a hybrid approach. In Language Processing and Knowledge in the Web (pp. 104-110). Springer Berlin Heidelberg.
47
Nakajima, Y., Ptaszynski, M., Honma, H., & Masui, F. Extracting References to the Future from News using Morphosemantic Patterns.
48
De conception, d. d. i. etiquetage morphosyntaxique du yoruba standard, une langue de la famille niger-congo et perspectives pour les langues nationales du benin.
49
Adedjouma Sèmiyou, A., Aoga, J. O., & Igue, M. A. (2013). Part-of-speech tagging of yoruba standard, language of niger-congo family. Res. Journal of Computer & IT Sciences, 1(1), 2-5.
50
Tamburini, F. (2013). The AnIta-Lemmatiser: A Tool for Accurate Lemmatisation of Italian Texts. In Evaluation of Natural Language and Speech Tools for Italian (pp. 266-273). Springer Berlin Heidelberg.
51
Nigussie, E. (2013). Afaan Oromo–Amharic Cross Lingual Information Retrieval (Doctoral dissertation, AAU).
52
Misikir, T. (2013). Developing a Stemming Algorithm for Awngi Text (Doctoral dissertation, AAU).
53
Khanam, M. H. experiments in probabilistic context free grammar for urdu language.
54
Ptaszynski, M., Dybala, P., Mazur, M., Rzepka, R., Araki, K., & Momouchi, Y. (2013). Towards Computational Fronesis: Verifying Contextual Appropriateness of Emotions. International Journal of Distance Education Technologies (IJDET), 11(2), 16-47.
55
Ptaszynski, M. Taking Affect Analysis One Step Higher: The Idea of Contextual Appropriateness of Emotions and Its Perspectives.
56
Chopra, D., & Morwal, S. (2013). Named Entity Recognition in English Using Hidden Markov Model. International Journal.
57
Morwal, S., & Chopra, D. (2013). nerhmm: A Tool For Named Entity Recognition based on Hidden Markov Model. International Journal on Natural Language Computing (IJNLC), 2, 43-49.
58
Christensen, H., Green, P. D., & Hain, T. (2013, August). Learning speaker-specific pronunciations of disordered speech. In Interspeech (pp. 1159-1163).
59
Sarker, M. Z. H., Ali, M. N. Y., & Das, J. K. Generation Rules to Deconvert UNL Expressions to Bangla Sentences.
60
Ptaszynski, M., Dokoshi, H., Oyama, S., Rzepka, R., Kurihara, M., Araki, K., & Momouchi, Y. (2013). Affect analysis in context of characters in narratives. Expert Systems with Applications, 40(1), 168-176.
61
Agrawal, A. J., & Kakde, O. G. (2013). Semantic analysis of natural language queries using domain ontology for information access from database. International Journal of Intelligent Systems and Applications (IJISA), 5(12), 81.
62
Ptaszynski, M., Masui, F., Dybala, P., Rzepka, R., & Araki, K. Open Source Affect Analysis System with Extensions.
63
Prasad, T. V., & Muthukumaran, G. M. Telugu to English Translation using Direct Machine Translation Approach.
64
Nagarsekar, U., Mhapsekar, A., Kulkarni, P., & Kalbande, D. R. (2013, December). Emotion detection from “the SMS of the internet”. In Intelligent Computational Systems (RAICS), 2013 IEEE Recent Advances in (pp. 316-321). IEEE.
65
Sathyanarayana, S. A. S. A Hybrid approach for Named Entity Recognition, Classification and Extraction (NERCE) in Kannada Documents.
66
ABEDO, M. K. (2012). school of graduates studies department of information science (Doctoral dissertation, Addis Ababa University).
67
Lempa, P., Ptaszynski, M., & Masui, F. Cyberbullying Blocker Application for Android.
68
Ptaszynski, M., Masui, F., Kimura, Y., Rzepka, R., & Araki, K. Extracting Patterns of Harmful Expressions for Cyberbullying Detection.
69
Chopra, D., Morwal, S., & Purohit, G. N. hidden markov model based named entity recognition tool.
70
Tamburini, F., & Melandri, M. (2012). AnIta: a powerful morphological analyser for Italian. In LREC (pp. 941-947).
71
Morwal, S., Jahan, N., & Chopra, D. (2012). Named entity recognition using hidden Markov model (HMM). International Journal on Natural Language Computing (IJNLC), 1(4).
72
Althobaiti, M., Kruschwitz, U., & Poesio, M. (2012, September). Identifying named entities on a university intranet. In Computer Science and Electronic Engineering Conference (CEEC), 2012 4th (pp. 94-99). IEEE.
73
D’hondt, E., Verberne, S., Weber, N., Koster, C., & Boves, L. (2012). Using skipgrams and pos-based feature selection for patent classification. Computational Linguistics in the Netherlands Journal, 2, 52-70.
74
Chopra, D., & Morwal, S. (2012). Named Entity Recognition in Punjabi Using Hidden Markov Model. International Journal of Computer Science & Engineering Technology (IJCSET), 3(12).
75
Ptaszynski, M., Hasegawa, D., & Masui, F. Women Like Backchannel, But Men Finish Earlier: Pattern Based Language Modeling of Conversations Reveals Gender and Social Distance Differences.
76
Abbas, Q. (2012). Building a hierarchical annotated corpus of urdu: the URDU. KON-TB treebank. In Computational Linguistics and Intelligent Text Processing (pp. 66-79). Springer Berlin Heidelberg.
77
Jahangir, F., Anwar, W., Bajwa, U. I., & Wang, X. (2012, December). N-gram and gazetteer list based named entity recognition for urdu: A scarce resourced language. In Proceedings of the 10th Workshop on Asian Language Resources (pp. 95-104).
78
Jahan, N., Morwal, S., & Chopra, D. (2012). Named entity recognition in indian languages using gazetteer method and hidden markov model: A hybrid approach. IJCSET, March.
79
Chopra, D., Jahan, N., & Morwal, S. (2012). Hindi named entity recognition by aggregating rule based heuristics and hidden markov model. International Journal of Information Sciences and Techniques (IJIST) Vol, 2.
80
Tamburini, F. (2011). The anita-lemmatiser. Working Notes of EVALITA.
81
Kumar, D. stemming of punjabi words by using brute force technique Dinesh Kumar Assistant Prof. & Head Department of Information Technology daviet, Jalandhar Prince Rana.
82
YONAS, F. (2011). Development of stemming algorithm for Tigrigna text.
83
Tesfaye, D. (2011). A rule-based Afan Oromo Grammar Checker. IJACSA Editorial.
84
Harrathi, R., Ouni, C., & Farhat, M. Impact de l’intégration de l’analyse morphologique de la langue arabe dans un système de recherche d’information open source.
85
HENOK, B. (2011). Dsp based impelementation of field-weakening on synchronous motor for high speed operation (doctoral dissertation, aau).
86
Kumar, D., & Rana, P. (2011). Stemming of Punjabi Words by using Brute Force Technique. International Journal of Engineering Science and Technology (IJEST) Vol, 3, 1351-1357.
87
Fisseha, Y. (2011). Development of Stemming Algorithm for Tigrgna Text (Doctoral dissertation, AAU).
88
Abbas, Q. (2014). Building Computational Resources: The URDU. KON-TB Treebank and the Urdu Parser (Doctoral dissertation).
89
Abbas, Q. Morphologically rich Urdu grammar parsing using Earley algorithm. Natural Language Engineering, 1-36.
90
Abbas, Q. (2014). Building Computational Resources: The URDU. KON-TB Treebank and the Urdu Parser (Doctoral dissertation).
91
Abbas, Q. Morphologically rich Urdu grammar parsing using Earley algorithm. Natural Language Engineering, 1-36.