Author: perezparedes

Video: How to Merge Text (.Txt) Files in Command Prompt (Windows)

Post author By perezparedes
Post date 22nd September 2014

Click above

If you have a bunch of text files in a folder on your computer which you’d like to merge together, you can simply do just that with one easy command in Windows Command Prompt. This will help with various things including word lists, dictionaries and help clean up your folder a little more.

CFP Research in Corpus Linguistics (RiCL)

Post author By perezparedes
Post date 21st September 2014

Call for papers

Research in Corpus Linguistics (RiCL)

(official journal of the Spanish Association for Corpus Linguistics AELINCO, published by Academy Publisher)

Research in Corpus Linguistics (RiCL, ISSN 2243-4712) is a peer-reviewed international scientific journal published annually, aiming at the publication of original research based on corpus data from different languages and language families and from different theoretical perspectives and frameworks, with the goal of improving our knowledge about the grammar and the linguistic theoretical background of a language, a language family or any type of cross-linguistic phenomena/constructions/assumptions.

RiCL invites previously unpublished research articles and book reviews in the field of corpus linguistics. Specific areas of interest include corpus design, compilation and typology; discourse, literary analysis and corpora; corpus-based grammatical studies; corpus-based lexicology and lexicography; corpora, contrastive studies and translation; corpus and linguistic variation; corpus-based computational linguistics; corpora, language acquisition and teaching; and special uses of corpus linguistics. The journal also publishes special issues on specific topics, with leading specialists in the field of corpus linguistics as guest editors.

Editors: Javier Pérez-Guerra (University of Vigo) and María José López-Couso (University of Santiago de Compostela)

Links:
– journal website: http://www.academypublisher.com/ricl/
– past issue: http://ojs.academypublisher.com/index.php/ricl/issue/archive
– instructions for authors: http://www.academypublisher.com/ricl/authorguide.html

Subjects at UMU

Ten of the best collective nouns

Post author By perezparedes
Post date 20th September 2014

From a murder of crows to a misbelief of painters, Chloe Rhodes investigates the intriguing origins of her favourite collective nouns

Source: www.theguardian.com

See on Scoop.it – Applied linguistics and knowledge engineering

academics Quotes and power ideas universidad

La Universidad tóxica

Post author By perezparedes
Post date 19th September 2014

Fotografía de Patricio Alcaraz1 (Flickr )

Recomiendo la lectura de este artículo sobe el trabajo del profesor universitario publicado El Conficencial. Contiene, eso sí, algunas opiniones y generalizaciones que no comparto en absoluto por simplistas, quizá por influencia del populismo imperante en el discurso en los medios,

computational linguistics discourse structure in scholarly discourse NLP summarization

Release of SciSumm14 an annotated corpus for scientific summarization.

Post author By perezparedes
Post date 19th September 2014

From the Corpora list
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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:

https://github.com/WING-NUS/scisumm-corpus

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:

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ACL-anthology-id Tile of the paper

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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