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Found 19 papers, 1 papers with code
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models
We show that providing the model with word-level features bridges the gap for the neural network approach to achieve a state-of-the-art F1 score on a standard Arabic language correction shared task dataset.
Addressing Noise in Multidialectal Word Embeddings
Arabic dialects lack large corpora and are noisy, being linguistically disparate with no standardized spelling.
A Parallel Corpus for Evaluating Machine Translation between Arabic and European Languages
We present Arab-Acquis, a large publicly available dataset for evaluating machine translation between 22 European languages and Arabic.
Noise-Robust Morphological Disambiguation for Dialectal Arabic
User-generated text tends to be noisy with many lexical and orthographic inconsistencies, making natural language processing (NLP) tasks more challenging.
Don't Throw Those Morphological Analyzers Away Just Yet: Neural Morphological Disambiguation for Arabic
We make use of the resulting morphological models for scoring and ranking the analyses of the morphological analyzer for morphological disambiguation.
Analysis of Foreign Language Teaching Methods: An Automatic Readability Approach
Much research in education has been done on the study of different language teaching methods.
YAMAMA: Yet Another Multi-Dialect Arabic Morphological Analyzer
In this paper, we present YAMAMA, a multi-dialect Arabic morphological analyzer and disambiguator.
Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging
Semitic languages can be highly ambiguous, having several interpretations of the same surface forms, and morphologically rich, having many morphemes that realize several morphological features.
Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling
In this paper we explore the use of multitask learning and adversarial training to address morphological richness and dialectal variations in the context of full morphological tagging.
Unsupervised Neologism Normalization Using Embedding Space Mapping
This paper presents an approach for detecting and normalizing neologisms in social media content.
Morphological Analysis and Disambiguation for Gulf Arabic: The Interplay between Resources and Methods
In this paper we present the first full morphological analysis and disambiguation system for Gulf Arabic.
AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding
However, this approach constrains knowledge sharing across different attributes.
PAM: Understanding Product Images in Cross Product Category Attribute Extraction
Understanding product attributes plays an important role in improving online shopping experience for customers and serves as an integral part for constructing a product knowledge graph.
End-to-End Conversational Search for Online Shopping with Utterance Transfer
Successful conversational search systems can present natural, adaptive and interactive shopping experience for online shopping customers.
Utilizing Subword Entities in Character-Level Sequence-to-Sequence Lemmatization Models
In addition to generic n-gram embeddings (using FastText), we experiment with concatenative (stems) and templatic (roots and patterns) morphological subwords.
PV2TEA: Patching Visual Modality to Textual-Established Information Extraction
Information extraction, e. g., attribute value extraction, has been extensively studied and formulated based only on text.
