Search Results for author: Behrang Qasemizadeh

Found 18 papers, 1 papers with code

Sketching Word Vectors Through Hashing

1 code implementation11 May 2017 Behrang QasemiZadeh, Laura Kallmeyer

We propose a new fast word embedding technique using hash functions.

Challenges in Persian Electronic Text Analysis

no code implementations18 Apr 2014 Behrang QasemiZadeh, Saeed Rahimi, Mehdi Safaee Ghalati

Farsi, also known as Persian, is the official language of Iran and Tajikistan and one of the two main languages spoken in Afghanistan.

The First Parallel Multilingual Corpus of Persian: Toward a Persian BLARK

no code implementations17 Apr 2014 Behrang Qasemizadeh, Saeed Rahimi, Behrooz Mahmoodi Bakhtiari

In this article, we have introduced the first parallel corpus of Persian with more than 10 other European languages.

HHU at SemEval-2017 Task 2: Fast Hash-Based Embeddings for Semantic Word Similarity Assessment

no code implementations SEMEVAL 2017 Behrang QasemiZadeh, Laura Kallmeyer

This paper describes the HHU system that participated in Task 2 of SemEval 2017, Multilingual and Cross-lingual Semantic Word Similarity.

Learning Word Embeddings Semantic Textual Similarity +2

TRAPACC and TRAPACCS at PARSEME Shared Task 2018: Neural Transition Tagging of Verbal Multiword Expressions

no code implementations COLING 2018 Regina Stodden, Behrang Qasemizadeh, Laura Kallmeyer

We describe the TRAPACC system and its variant TRAPACCS that participated in the closed track of the PARSEME Shared Task 2018 on labeling verbal multiword expressions (VMWEs).

Dimensionality Reduction Lexical Analysis

A Study on the Interplay Between the Corpus Size and Parameters of a Distributional Model for Term Classification

no code implementations WS 2016 Behrang QasemiZadeh

We propose and evaluate a method for identifying co-hyponym lexical units in a terminological resource.

General Classification

Semi-Supervised Technical Term Tagging With Minimal User Feedback

no code implementations LREC 2012 Behrang QasemiZadeh, Paul Buitelaar, Tianqi Chen, Georgeta Bordea

In this paper, we address the problem of extracting technical terms automatically from an unannotated corpus.

Dependency Parsing Language Modelling +1

SemEval-2019 Task 2: Unsupervised Lexical Frame Induction

no code implementations SEMEVAL 2019 Behrang QasemiZadeh, Miriam R. L. Petruck, Regina Stodden, Laura Kallmeyer, C, Marie ito

This paper presents Unsupervised Lexical Frame Induction, Task 2 of the International Workshop on Semantic Evaluation in 2019.

Clustering Task 2

The ACL RD-TEC 2.0: A Language Resource for Evaluating Term Extraction and Entity Recognition Methods

no code implementations LREC 2016 Behrang QasemiZadeh, Anne-Kathrin Schumann

To assess the quality of the annotations and to determine the difficulty of this annotation task, more than 171 of the abstracts are annotated twice, independently, by each of the two annotators.

Term Extraction

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