Ranking & Metrics
Impact Score is a novel metric devised to rank conferences based on the number of contributing the best scientists in addition to the h-index estimated from the scientific papers published by the best scientists. See more details on our methodology page.
Research Impact Score:7.60
Contributing Best Scientists:181
H5-index:
Papers published by Best Scientists272
Research Ranking (Computer Science)45
Research Ranking (Computer Science)36
Conference Call for Papers
All papers accepted for full oral presentation at CICLing 2018 will be published in a proceedings volume edited by Springer in its Lecture Notes in Computer Science series, which is indexed in many major indices including Scopus. Papers accepted for short oral presentation plus poster presentation will be published separately in special issues of journals, see Poster Session (let us know if you actually prefer this type of publication).
In addition to the text of the paper, authors are strongly encouraged to provide code and data that permit to reproduce their results, see CICLing verifiability, reproducibility, and working description policy.
Before submitting, please check our legal notices on video recording and on obligations of authors. In particular, by submitting a paper, at least one author thereby promises, in case of acceptance, to attend the conference in person to present the paper (if possible) and to pay the corresponding registration fee. Submissions are received electronically.
Overview
Top Research Topics at International Conference on Computational Linguistics?
Artificial intelligence (72.41%)
Natural language processing (64.08%)
Task (project management) (15.34%)
International Conference on Computational Linguistics mainly tackles studies in Artificial intelligence, Natural language processing, Task (project management), Parsing and Information retrieval.
The study on Artificial intelligence presented in the event intersects with subjects under the field of Speech recognition.
The research on Natural language processing tackled can also make contributions to studies in the areas of Context (language use), SemEval and Grammar.
Sentiment analysis, Machine learning and Identification (information) are some topics wherein Task (project management) research discussed in the conference have an impact.
The study of Parsing, which falls within the realm of Programming language, was the main focus of the presentations.
Most of the Machine translation studies addressed also intersect with Translation (geometry).
What are the most cited papers published at the conference?
Automatic acquisition of hyponyms from large text corpora (2942 citations)
Determining the sentiment of opinions (1242 citations)
Message Understanding Conference-6: a brief history (1058 citations)
Research areas of the most cited articles at International Conference on Computational Linguistics:
The main points discussed in the most cited articles deal with Artificial intelligence, Natural language processing, Task (project management), Parsing and Sentence.
The most cited articles explore topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning, Speech recognition and Information retrieval.
The conference articles focus on Natural language processing but the discussions also offer insight into other areas such as Set (abstract data type) and Grammar.
What topics the last edition of the conference is best known for?
Artificial intelligence
Natural language processing
Machine learning
The previous edition focused in particular on these issues:
The conference was organized to reinforce research efforts on Artificial intelligence, Natural language processing, Task (project management), SemEval and Language model.
While Artificial intelligence is the focus of International Conference on Computational Linguistics, it also provided insights into the studies of Context (language use) and Machine learning.
International Conference on Computational Linguistics addresses concerns in Natural language processing which are intertwined with other disciplines, such as Social media and Identification (information).
The event explores issues in Task (project management) which can be linked to other research areas like Domain (software engineering), Artificial neural network, Deep learning, Transfer of learning and Natural language.
In the event, Semantic change, Offensive, Propaganda techniques, Ranking and Arabic are investigated in conjunction with one another to address concerns in SemEval research.
The research on Offensive featured in the event combines topics in other fields like Danish and Turkish.
The most cited articles from the last conference are:
SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020) (189 citations)
SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets (72 citations)
Papers citation over time
A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
Research.com
Top authors and change over time
The top authors publishing at International Conference on Computational Linguistics (based on the number of publications) are:
Pushpak Bhattacharyya (37 papers) published 8 papers at the last edition, 5 more than at the previous edition,
Ting Liu (35 papers) published 4 papers at the last edition the same number as at the previous edition,
Jun'ichi Tsujii (35 papers) published 1 paper at the last edition,
Guodong Zhou (35 papers) published 4 papers at the last edition, 5 less than at the previous edition,
Hsin-Hsi Chen (33 papers) published 2 papers at the last edition, 2 less than at the previous edition.
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Research.com
Top affiliations and change over time
Only papers with recognized affiliations are considered
The top affiliations publishing at International Conference on Computational Linguistics (based on the number of publications) are:
IBM (167 papers) published 26 papers at the last edition, 11 more than at the previous edition,
Microsoft (133 papers) published 29 papers at the last edition, 21 more than at the previous edition,
Carnegie Mellon University (108 papers) published 11 papers at the last edition, 4 less than at the previous edition,
Chinese Academy of Sciences (106 papers) published 33 papers at the last edition, 17 more than at the previous edition,
University of Stuttgart (103 papers) published 9 papers at the last edition, 2 more than at the previous edition.
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
Research.com
Publication chance based on affiliation
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
Research.com
During the most recent 2020 edition, 11.98% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 17.89% were posted by at least one author from the top 10 institutions publishing at the conference. Another 6.04% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.31% of all publications and 64.76% were from other institutions.
Returning Authors Index
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.
Research.com
Returning Institution Index
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Research.com
The experience to innovation index
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
