Category: NLP

Most Relevant NLP Journals via NLPeople

This is a question and follow-up initiated by Eduardo César Garrido Merchán in the Linkedin NLPeople group.

Meeting of the Association for Computational Linguistics (ACL)
Transactions of the Association for Computational Linguistics (ISSN: 2307-387X)
European Chapter of the ACL (EACL)
North American Chapter of the Association for Computational Linguistics
International Conference on Computational Linguistics (COLING)
Conference on Empirical Methods in Natural Language Processing (EMNLP)
Data & Knowledge Engineering.
IEEE Transactions on Knowledge and Data Engineering
Computational Linguistics
International Conference on Computational Linguistics and Intelligent Text Processing
Text REtrieval Conference (TREC)
International Joint Conference on Natural Language Processing
SIGIR
ECIR
CICLing.org

NLP conference calendar: http://www.cs.rochester.edu/~tetreaul/conferences.html

CFP | KESA 2015 | April 19 – 24, 2015 – Barcelona Submission deadline November 24, 2015

CFP | KESA 2015 | April 19 – 24, 2015 – Barcelona, Spain
KESA 2015, The International Workshop on Knowledge Extraction and Semantic Annotation

Through LinkedIn Corpus linguistics Group

Please consider to contribute to and/or forward to the appropriate
groups the following opportunity to submit and publish original
scientific results to KESA 2015.
The submission deadline is November 24, 2014.
Authors of selected papers will be invited to submit extended article
versions to one of the IARIA Journals: http://www.iariajournals.org

============== KESA 2015 | Call for Contributions ===============

CALL FOR PAPERS, TUTORIALS, PANELS

KESA 2015, The International Workshop on Knowledge Extraction and Semantic Annotation
April 19 – 24, 2015 – Barcelona, Spain

General/submission page: http://www.iaria.org/conferences2015/KESA.html

Contribution types;
regular papers [in the proceedings, digital library]
short papers (work in progress) [in the proceedings, digital library]
ideas: two pages [in the proceedings, digital library]
extended abstracts: two pages [in the proceedings, digital library]
posters: two pages [in the proceedings, digital library]
posters: slide only [slide-deck posted on www.iaria.org]
presentations: slide only [slide-deck posted on www.iaria.org]
demos: two pages [posted on www.iaria.org]
doctoral forum submissions: [in the proceedings, digital library]

Submission deadline: November 24, 2015

Sponsored by IARIA, www.iaria.org

Extended versions of selected papers will be published in IARIA
Journals: http://www.iariajournals.org

Print proceedings will be available via Curran Associates, Inc.:
http://www.proceedings.com/9769.html

Articles will be archived in the free access ThinkMind Digital Library:
http://www.thinkmind.org

The topics suggested by the conference can be discussed in term of
concepts, state of the art, research, standards, implementations,
running experiments, applications, and industrial case studies. Authors
are invited to submit complete unpublished papers, which are not under
review in any other conference or journal in the following, but not
limited to, topic areas.

All tracks are open to both research and industry contributions.

Before submission, please check and comply with the editorial rules:
http://www.iaria.org/editorialrules.html

KESA 2015 Topics (topics and submission details: see on the site)

Shallow knowledge extraction from large collections
Knowledge and ontology management
Knowledge acquisition from unstructured data
Concepts and standards for semantic annotation
Ontology learning
Semantic knowledge
Mining for topic annotation
Context and semantic annotation
User-centric semantic annotation
Semantic retrieval and annotation
Linguistic Linked Open Data
Methods in text and data mining
Interactive image searching
—————————-

KESA 2015 Co-Chairs
Maria Pia di Buono, University of Salerno, Italy
Mario Monteleone, University of Salerno, Italy
Annibale Elia, University of Salerno, Italy
===============================================

Release of SciSumm14 an annotated corpus for scientific summarization.

From the Corpora list
::::::::::::::::::::::::::::::::::

SciSumm14 is an open repository with a corpus of ACL Computational Linguistics research papers and their annotations, contributed to the public by the Web IR / NLP Group at the National University of Singapore (WING-NUS).  This corpus is offered as a part of the SciSumm Shared Task in TAC 2014. The SciSumm Shared Task is organized under the BiomedSumm track. It follows the basic structure and guidelines of the Biomedical Summarization Track and adapts them for annotating and creating a corpus of training topics from computational linguistics (CL) research papers. 

The purpose behind the release of this corpus is to highlight the challenges and relevance of the scientific summarization problem, support research in automatic scientific document summarization and provide evaluation resources to push the current state of the art. This corpus offers a “community” summary of a reference paper based on its collection of citing sentences, called citances. Furthermore, each of the citances is mapped to referenced text in the reference paper and tagged with the information facet it represents.
This corpus is expected to be of interest to a broad community including those working in computational linguistics NLP, text summarization, discourse structure in scholarly discourse, paraphrase, textual entailment, and/or text simplification.
WEBSITE AND COMPLETE CALL:
CORPUS MAINTENANCE:
Dr. Kokil Jaidka (Wee Kim Wee School of Communication and Information, Nanyang Technological University)koki0001@e.ntu.edu.sg
Dr. Min-Yen Kan (Dept. of Computer Science, School of Computing, National University of Singapore)kanmy@comp.nus.edu.sg
Muthu Kumar Chandrasekaran (Dept. of Computer Science, School of Computing, National University of Singapore)muthu.chandra@comp.nus.edu.sg
Ankur Khanna (Web, IR/NLP group, National University of Singapore) khanna89ankur@gmail.com
SUMMARY OF CORPUS PROPERTIES:
​1. Created by randomly sampling ten documents from the ACL Anthology corpus and selecting their citing papers. It is available for download at https://github.com/WING-NUS/scisumm-corpus
2. Organized into “topic” folders. Each “topic” is the Reference Paper, and the folder contains upto ten Citing Papers (CPs) that all contain citations to the RP. In each CP, the text spans (i.e., citances) have been identified that pertain to a particular citation to the RP.
3. Most text files were created from the pdf files obtained above by using Adobe Acrobat. The remaining were converted using the GATE 8.0 open source software. For more details, see the README at https://github.com/WING-NUS/scisumm-corpus
4. Inter-annotator agreement was used to assess the homogeneity and quality of the coding of citances and references, and disagreements were resolved through discussion.
5. The ACL ids and the titles of reference papers are given below:
————————————–
ACL-anthology-id     Tile of the paper
————————————–
H89-2014                   Augmenting a Hidden Markov Model for Phrase-Dependent Word Tagging
X96-1048                    OVERVIEW OF RESULTS OF THE MUC-6 EVALUATION 
C94-2154                    THE CORRECT AND EFFICIENT IMPLEMENTATION OF APPROPRIATENESS SPECIFICIATIONS FOR TYPED FEATURE STRUCTURES
E03-1020                    Discovering Corpus-Specific Word Senses
C90-2039                    Strategic Lazy Incremental Copy Graph Unification
J00-3003                     Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech
P98-1081                    Improving Data Driven Wordclass Tagging by System Combination
N01-1011                    A Decision Tree of Bigrams is an Accurate Predictor of Word Sense
H05-1115                    Using Random Walks for Question-focused Sentence Retrieval
J98-2005                     Estimation of Probabilistic Context-Free Grammars

Language Processing with Perl and Prolog, 2nd edition @Springer

Language Processing with Perl and Prolog, 2nd edition
By Pierre Nugues
Published by Springer

This book has a companion website at http://ilppp.cs.lth.se/
and can be ordered from Springer: http://www.springer.com/978-3-642-41463-3
or Amazon: http://www.amazon.com/Language-Processing-Perl-Prolog-Implementation/dp/364241463X/

Overview:
This book teaches the principles of natural language processing, first covering practical linguistics issues such as encoding and annotation schemes, defining words, tokens and parts of speech, and morphology, as well as key concepts in machine learning, such as entropy, regression, and classification, which are used throughout the  book. It then details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques, using Prolog to write phase-structure grammars, syntactic formalisms and constituent and dependency parsing techniques, semantics, predicate logic, and lexical semantics, and analysis of discourse and applications in dialogue systems. A key feature of the book is the author’s hands-on approach throughout, with sample code in Prolog and Perl, extensive exercises, and a detailed introduction to Prolog. The reader is supported with a companion website that contains teaching slides, programs, and additional material.

The second edition is a complete revision of the techniques exposed in the first edition to reflect advances in the field. The author redesigned or updated all the chapters, added two new ones, and considerably expanded the sections on machine-learning techniques.

Contents:
1 An Overview of Language Processing
2 Corpus Processing Tools
3 Encoding and Annotation Schemes
4 Topics in Information Theory and Machine Learning
5 Counting Words
6 Words, Parts of Speech, and Morphology
7 Part-of-Speech Tagging Using Rules
8 Part-of-Speech Tagging Using Statistical Techniques
9 Phrase-Structure Grammars in Prolog
10 Partial Parsing
11 Syntactic Formalisms
12 Constituent Parsing
13 Dependency Parsing
14 Semantics and Predicate Logic
15 Lexical Semantics
16 Discourse
17 Dialogue
Appendix: An Introduction to Prolog
Index
References