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ACM Transactions on Asian Language Information Processing is a peer-reviewed journal published by ACM, covering Natural Language Processing Techniques, Topic Modeling, Speech and dialogue systems.
| Publisher | ACM |
|---|---|
| Reference style | Numbered (ACM) Numbered — [1], [2] in the text [1] Ada Smith, Ben Jones, and Cara Lee. 2023. A representative article title. ACM Transactions on Asian Language Information Processing 12, 3, Article 45 (2023).
Formats any DOI in ACM Transactions on Asian Language Information Processing style. No sign-up. |
| Publishes research in | Natural Language Processing Techniques Topic Modeling Speech and dialogue systems Speech Recognition and Synthesis Text and Document Classification Technologies |
| ISSN | 1530-0226 |
| h-index | 35 |
| i10-index | 144 |
| Total citations | 6,042 |
| Top institutions publishing here | Pohang University of Science and Technology |
| Journal website | portal.acm.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
The Arabic language presents researchers and developers of natural language processing (NLP) applications for Arabic text and speech with serious challenges. The purpose of this article is to describe some of these challenges and to present some solutions that would guide current and future practitioners in the field of Arabic natural language processing (ANLP). We…
In connection with the DAML project for bringing about the Semantic Web, an ontology of time is being developed for describing the temporal content of Web pages and the temporal properties of Web services. This ontology covers topological properties of instants and intervals, measures of duration, and the meanings of clock and calendar terms.
This paper evaluates five supervised learning methods in the context of statistical spam filtering. We study the impact of different feature pruning methods and feature set sizes on each learner's performance using cost-sensitive measures. It is observed that the significance of feature selection varies greatly from classifier to classifier. In particular, we found support vector…
This study presents a novel approach to automatic emotion recognition from text. First, emotion generation rules (EGRs) are manually deduced from psychology to represent the conditions for generating emotion. Based on the EGRs, the emotional state of each sentence can be represented as a sequence of semantic labels (SLs) and attributes (ATTs); SLs are defined…
Stemming words to (usually) remove suffixes has applications in text search, machine translation, document summarization, and text classification. For example, English stemming reduces the words "computer," "computing," "computation," and "computability" to their common morphological root, "comput-." In text search, this permits a search for "computers" to find documents containing all words with the stem "comput-."…
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