| 2 |
Introducing Various Semantic Models for Amharic: Experimentation and Evaluation with Multiple Tasks and Datasets
|
|
|
|
In: Future Internet ; Volume 13 ; Issue 11 (2021)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Using Semantics for Granularities of Tokenization
|
|
|
|
In: Computational Linguistics, Vol 44, Iss 3, Pp 483-524 (2018) (2018)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph-based Word Sense Induction
|
|
|
|
BASE
|
|
Show details
|
|
|
| 6 |
Webbasierte linguistische Forschung: Möglichkeiten und Begrenzungen beim Umgang mit Massendaten
|
|
|
|
In: Linguistik Online, Vol 61, Iss 4 (2014) (2014)
|
|
BASE
|
|
Show details
|
|
|
| 7 |
SemEval-2013 task 5: Evaluating phrasal semantics
|
|
|
|
In: http://www.aclweb.org/anthology/S/S13/S13-2007.pdf (2013)
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Using Distributional Similarity for Lexical Expansion in Knowledge-based Word Sense Disambiguation
|
|
|
|
In: http://aclweb.org/anthology/C/C12/C12-1109.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 9 |
Ukp: Computing semantic textual similarity by combining multiple content similarity measures
|
|
|
|
In: http://aclweb.org/anthology//S/S12/S12-1059.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 10 |
Quantifying semantics using complex network analysis
|
|
|
|
In: http://aclweb.org/anthology/C/C12/C12-1017.pdf (2012)
|
|
BASE
|
|
Show details
|
|
|
| 11 |
ASV Toolbox – A Modular Collection of Language Exploration Tools
|
|
|
|
In: http://asv.informatik.uni-leipzig.de/publication/file/94/biemann-etal-08-toolbox.pdf (2008)
|
|
BASE
|
|
Show details
|
|
|
| 12 |
ASV Toolbox – A Modular Collection of Language Exploration Tools
|
|
|
|
In: http://www.lrec-conf.org/proceedings/lrec2008/pdf/447_paper.pdf (2008)
|
|
BASE
|
|
Show details
|
|
|
| 13 |
workshop on Graph-based Algorithms for Natural Language Processing Workshop chairs:
|
|
|
|
In: http://www.aclweb.org/anthology-new/W/W08/W08-20.pdf (2008)
|
|
BASE
|
|
Show details
|
|
|
| 14 |
Unsupervised part-of-speech tagging employing efficient graph clustering
|
|
|
|
In: http://wortschatz.uni-leipzig.de/~cbiemann/pub/2006/unsupos_graph_coling06SRW.pdf (2006)
|
|
BASE
|
|
Show details
|
|
|
| 15 |
Automatic extension of feature-based semantic lexicons via contextual attributes
|
|
|
|
In: http://pi7.fernuni-hagen.de/osswald/papers/gfkl05.pdf (2006)
|
|
BASE
|
|
Show details
|
|
|
| 16 |
Unsupervised part-of-speech tagging employing efficient graph clustering
|
|
|
|
In: http://acl.ldc.upenn.edu/P/P06/P06-3002.pdf (2006)
|
|
BASE
|
|
Show details
|
|
|
| 17 |
Unsupervised part-of-speech tagging employing efficient graph clustering
|
|
|
|
In: http://machinelearningtext.pbworks.com/w/file/fetch/48158637/UnsupPOSp7-biemann.pdf (2006)
|
|
BASE
|
|
Show details
|
|
|
| 18 |
Rigorous dimensionality reduction through linguistically motivated feature selection for text categorisation
|
|
|
|
In: http://wortschatz.uni-leipzig.de/~fwitschel/papers/nodalida.pdf (2005)
|
|
BASE
|
|
Show details
|
|
|
| 19 |
Disentangling from babylonian confusion – unsupervised language identification
|
|
|
|
In: http://wortschatz.uni-leipzig.de/~cbiemann/pub/2005/cicling05.pdf (2005)
|
|
Abstract:
Abstract: This work presents an unsupervised solution to language identification. The method sorts multilingual text corpora on the basis of sentences into the different languages that are contained and makes no assumptions on the number or size of the monolingual fractions. Evaluation on 7-lingual corpora and bilingual corpora show that the quality of classification is comparable to supervised approaches and works almost error-free from 100 sentences per language on. 1
|
|
URL: http://wortschatz.uni-leipzig.de/~cbiemann/pub/2005/cicling05.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.487.9943
|
|
BASE
|
|
Hide details
|
|
|
| 20 |
Automatic acquisition of paradigmatic relations using iterated co-occurrences
|
|
|
|
In: http://wortschatz.uni-leipzig.de/~sbordag/papers/BiemannBordagQuasthoffAutomatic04.pdf (2004)
|
|
BASE
|
|
Show details
|
|
|
|
|
