Besim Kabashi | Semantic Scholar

Publications
Influence

KLUE: Simple and robust methods for polarity classification

Thomas Proisl, Paul Greiner, Stefan Evert, Besim Kabashi

Computer Science

SemEval@NAACL-HLT

2013 (First Published: 1 June 2013)

This paper describes our approach to the SemEval-2013 task on “Sentiment Analysis in Twitter”. We use simple bag-of-words models, a freely available sentiment dictionary automatically extended with… Continue Reading

SentiKLUE: Updating a Polarity Classifier in 48 Hours

Stefan Evert, Thomas Proisl, Paul Greiner, Besim Kabashi

Computer Science

SemEval@COLING

2014 (First Published: 1 August 2014)

SentiKLUE is an update of the KLUE polarity classifier – which achieved good and robust results in SemEval-2013 with a simple feature set – implemented in 48 hours.

SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching

Thomas Proisl, Stefan Evert, Paul Greiner, Besim Kabashi

Computer Science

SemEval@COLING

2014 (First Published: 1 August 2014)

Being able to quantify the semantic similarity between two texts is important for many practical applications. SemantiKLUE combines unsupervised and supervised techniques into a robust system for… Continue Reading

JSLIM - Computational Morphology in the Framework of the SLIM Theory of Language

Johannes Handl, Besim Kabashi, Thomas Proisl, Carsten Weber

Computer Science

SFCM

2009 (First Published: 4 September 2009)

JSLIM is a software system for writing grammars in accordance with the SLIM theory of language. Written in Java, it is designed to facilitate the coding of grammars for morphology as well as for… Continue Reading

Translation Inference across Dictionaries via a Combination of Graph-based Methods and Co-occurrence Statistics

Thomas Proisl, Philipp Heinrich, Stefan Evert, Besim Kabashi

Mathematics, Computer Science

LDK Workshops

2017

This system description explains how to use several bilingual dictionaries and aligned corpora in order to create translation candidates for novel language pairs. It proposes (1) a graph-based… Continue Reading

A Proposal for a Part-of-Speech Tagset for the Albanian Language

Besim Kabashi, Thomas Proisl

Computer Science

LREC

2016

Part-of-speech tagging is a basic step in Natural Language Processing that is often essential. Labeling the word forms of a text with fine-grained word-class information adds new value to it and can… Continue Reading

KLUE-CORE: A regression model of semantic textual similarity

Paul Greiner, Thomas Proisl, Stefan Evert, Besim Kabashi

Computer Science

*SEM@NAACL-HLT

2013 (First Published: 1 June 2013)

This paper describes our system entered for the *SEM 2013 shared task on Semantic Textual Similarity (STS). We focus on the core task of predicting the semantic textual similarity of sentence pairs.… Continue Reading

Proceedings of TIAD-2019 Shared Task - Translation Inference Across Dictionaries co-located with the 2nd Language, Data and Knowledge Conference (LDK 2019), Leipzig, Germany, May 20, 2019

Jorge Gracia, Besim Kabashi, Ilan Kernerman

Computer Science

TIAD@LDK

2019

The second shared task for Translation Inference Across Dictionaries (TIAD 2019) is aimed at exploring methods and techniques for automatically generating new bilingual (and multilingual)… Continue Reading

Results of the Translation Inference Across Dictionaries 2019 Shared Task

Jorge Gracia, Besim Kabashi, Ilan Kernerman, Marta Lanau-Coronas, Dorielle Lonke

Computer Science

TIAD@LDK

2019

The objective of the Translation Inference Across Dictionaries (TIAD) shared task is to explore and compare methods and techniques that infer translations indirectly between language pairs, based on… Continue Reading

Albanian Part-of-Speech Tagging: Gold Standard and Evaluation

Besim Kabashi, Thomas Proisl

Computer Science

LREC

2018

In this paper, we present a gold standard corpus for Albanian part-of-speech tagging and perform evaluation experiments with different statistical taggers. The corpus consists of more than 31,000… Continue Reading