Asian and Low-Resource Language Information Processing (TALLIP)


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ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) - TALLIP Notes and Regular Papers, Volume 16 Issue 1, December 2016

Online Handwritten Gurmukhi Strokes Dataset Based on Minimal Set of Words
Sukhdeep Singh, Anuj Sharma, Indu Chhabra
Article No.: 1
DOI: 10.1145/2896318

The online handwriting data are an integral part of data analysis and classification research, as collected handwritten data offers many challenges to group handwritten stroke classes. The present work has been done for grouping handwritten...

Pairwise Comparative Classification for Translator Stylometric Analysis
Heba El-Fiqi, Eleni Petraki, Hussein A. Abbass
Article No.: 2
DOI: 10.1145/2898997

In this article, we present a new type of classification problem, which we call Comparative Classification Problem (CCP), where we use the term data record to refer to a block of instances. Given a single data record with n instances...

Improving Unsupervised Dependency Parsing with Knowledge from Query Logs
Xiuming Qiao, Hailong Cao, Tiejun Zhao
Article No.: 3
DOI: 10.1145/2903720

Unsupervised dependency parsing becomes more and more popular in recent years because it does not need expensive annotations, such as treebanks, which are required for supervised and semi-supervised dependency parsing. However, its accuracy is...

Boosting Neural POS Tagger for Farsi Using Morphological Information
Peyman Passban, Qun Liu, Andy Way
Article No.: 4
DOI: 10.1145/2934676

Farsi (Persian) is a low-resource language that suffers from the data sparsity problem and a lack of efficient processing tools. Due to their broad application in natural language processing tasks, part-of-speech (POS) taggers are one of those...

A Seed-Based Method for Generating Chinese Confusion Sets
Liangliang Liu, Cungen Cao
Article No.: 5
DOI: 10.1145/2933396

In natural language, people often misuse a word (called a “confused word”) in place of other words (called “confusing words”). In misspelling corrections, many approaches to finding and correcting misspelling errors are...

Improving Semantic Parsing with Enriched Synchronous Context-Free Grammars in Statistical Machine Translation
Junhui Li, Muhua Zhu, Wei Lu, Guodong Zhou
Article No.: 6
DOI: 10.1145/2963099

Semantic parsing maps a sentence in natural language into a structured meaning representation. Previous studies show that semantic parsing with synchronous context-free grammars (SCFGs) achieves favorable performance over most other alternatives....

Section: TALLIP Notes

Understanding Document Semantics from Summaries: A Case Study on Hindi Texts
Karthik Krishnamurthi, Vijayapal Reddy Panuganti, Vishnu Vardhan Bulusu
Article No.: 7
DOI: 10.1145/2956236

Summary of a document contains words that actually contribute to the semantics of the document. Latent Semantic Analysis (LSA) is a mathematical model that is used to understand document semantics by deriving a semantic structure based on patterns...