2015 First International Conference on Arabic Computational Linguistics (ACLing)最新文献

筛选
英文 中文
Increasing the Accuracy of Opinion Mining in Arabic 提高阿拉伯语意见挖掘的准确性
Sasi Atia, K. Shaalan
{"title":"Increasing the Accuracy of Opinion Mining in Arabic","authors":"Sasi Atia, K. Shaalan","doi":"10.1109/ACLING.2015.22","DOIUrl":"https://doi.org/10.1109/ACLING.2015.22","url":null,"abstract":"Opinion Mining is a raising research field of interest, with its different applications derived by market needs to analyze product reviews or to assess the public opinion, for political reasons, during presidential campaigns. In this paper, we address an approach for improving accuracy of Opinion Mining in Arabic. In order to conduct our study we need Arabic linguistic resources for opinion mining. Investigating the available resources we found that the OCA corpus is available and sufficient to prove our approach. Experimental results showed that applying different parameters of the machine learning classifiers on the OCA corpus leads to increasing the accuracy of the Arabic Opinion Mining.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114509920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
Towards Analyzing Saudi Tweets 分析沙特的推文
Nora Al-Twairesh, H. Al-Khalifa, A. Al-Salman
{"title":"Towards Analyzing Saudi Tweets","authors":"Nora Al-Twairesh, H. Al-Khalifa, A. Al-Salman","doi":"10.1109/ACLING.2015.23","DOIUrl":"https://doi.org/10.1109/ACLING.2015.23","url":null,"abstract":"Recently Arabic dialects are receiving attention from the NLP research community due to their high usage in social media. One of the challenges of sentiment analysis of social media is the use of dialects. Since our ongoing research is on sentiment analysis of Saudi tweets, we conduct a pilot study to discover the percentage of Modern Standard Arabic (MSA) use by Saudi tweeters. The preliminary results show that 80% of the tweets used in the study are in MSA. Some phenomena found about the use of dialect in Saudi tweets are highlighted.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124634168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Building a Corpus for Arabic Dialects Using Games with a Purpose 用有目的的游戏建立阿拉伯语方言语料库
Maya Osman, Caroline Sabty, Nada Sharaf, Slim Abdennadher
{"title":"Building a Corpus for Arabic Dialects Using Games with a Purpose","authors":"Maya Osman, Caroline Sabty, Nada Sharaf, Slim Abdennadher","doi":"10.1109/ACLING.2015.10","DOIUrl":"https://doi.org/10.1109/ACLING.2015.10","url":null,"abstract":"There is a huge gap between the written form of Arabic, Modern Standard Arabic (MSA), and the different spoken Arabic dialects due to the big number of dialects. In addition, most Arabic data-sets are formed for MSA content. Traditional ways of identifying dialects of texts are time and money consuming. In addition, due to the morphological complexity of Arabic, the gender of the speaker may change structure of an Arabic sentence. Thus, dialects hold rich information (such as the origin of the speaker and the gender of the addressee). A Game With A Purpose (GWAP) called \"3ammeya\" is implemented to identify the dialects of Arabic sentences along with their MSA translations. Moreover, through the game, the gender of the speaker addressee are classified. The collected data will help construct an expandable and cheap corpus for dialect identification and translation to MSA.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127874579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Automatic Expandable Large-Scale Sentiment Lexicon of Modern Standard Arabic and Colloquial 现代标准阿拉伯语和口语的自动扩展大规模情感词典
Hossam S. Ibrahim, Sherif M. Abdou, M. Gheith
{"title":"Automatic Expandable Large-Scale Sentiment Lexicon of Modern Standard Arabic and Colloquial","authors":"Hossam S. Ibrahim, Sherif M. Abdou, M. Gheith","doi":"10.1109/ACLING.2015.20","DOIUrl":"https://doi.org/10.1109/ACLING.2015.20","url":null,"abstract":"In subjectivity and sentiment analysis (SSA), there are two main requirements are necessary to improve sentiment analysis effectively in any language and genres, first, high coverage sentiment lexicon - where entries are tagged with semantic orientation (positive, negative and neutral) - second, tagged corpora to train the sentiment classifier. Much of research has been conducted in this area during the last decade, but the need of building these resources is still ongoing, especially for morphologically-Rich language (MRL) such as Arabic. In this paper, we present an automatic expandable wide coverage polarity lexicon of Arabic sentiment words, this lexical resource explicitly devised for supporting Arabic sentiment classification and opinion mining applications. The lexicon is built using a seed of gold-standard Arabic sentiment words which are manually collected and annotated with semantic orientation (positive or negative), and automatically expanded with sentiment orientation detection of the new sentiment words by exploiting some lexical information such as part-of-speech (POS) tags and using synset aggregation techniques from free online Arabic lexicons, thesauruses. We report efforts to expand a manually-built our polarity lexicon using different types of data. Finally, we used various tagged data to evaluate the coverage and quality of our polarity lexicon, moreover, to evaluate the lexicon expansion and its effects on the sentiment analysis accuracy. Our data focus on modern standard Arabic (MSA) and Egyptian dialectal Arabic tweets and Arabic microblogs (hotel reservation, product reviews, and TV program comments).","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124902886","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Arabic Natural Language Processing from Software Engineering to Complex Pipeline 从软件工程到复杂管道的阿拉伯自然语言处理
Younes Jaafar, Karim Bouzoubaa
{"title":"Arabic Natural Language Processing from Software Engineering to Complex Pipeline","authors":"Younes Jaafar, Karim Bouzoubaa","doi":"10.1109/ACLING.2015.11","DOIUrl":"https://doi.org/10.1109/ACLING.2015.11","url":null,"abstract":"Arabic Natural Language Processing (ANLP) has known an important development during the last decade. Nowadays, Several ANLP tools are developed such as morphological analyzers, syntactic parsers, etc. These tools are characterized by their diversity in terms of development languages used, inputs/outputs manipulated, internal and external representations of results, etc. This is mainly due to the lack of models and standards that govern their implementations. This diversity does not favor interoperability between these tools or their reuse in new advanced projects. In this article, we propose APIs and models for three types of tools namely: stemmers, morphological analyzers and syntactic parsers, using SAFAR platform. Our proposal is a step for standardizing all aspects shared by tools of the same type. We review also the issue of interoperability between these tools. Finally, we discuss pipeline processes.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127669776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Semantic Based Query Expansion for Arabic Question Answering Systems 基于语义的阿拉伯语问答系统查询扩展
Hani Al-Chalabi, S. Ray, K. Shaalan
{"title":"Semantic Based Query Expansion for Arabic Question Answering Systems","authors":"Hani Al-Chalabi, S. Ray, K. Shaalan","doi":"10.1109/ACLING.2015.25","DOIUrl":"https://doi.org/10.1109/ACLING.2015.25","url":null,"abstract":"Question Answering Systems have emerged as a good alternative to search engines where they produce the desired information in a very precise way in the real time. However, one serious concern with the Question Answering system is that despite having answers of the questions in the knowledge base, they are not able to retrieve the answer due to mismatch between the words used by users and content creators. There has been a lot of research in the field of English and some European language Question Answering Systems to handle this issue. However, Arabic Question Answering Systems could not match the pace due to some inherent difficulties with the language itself as well as due to lack of tools available to assist the researchers. In this paper, we are presenting a method to add semantically equivalent keywords in the questions by using semantic resources. The experiments suggest that the proposed research can deliver highly accurate answers for Arabic questions.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132754531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 21
Toward the Resolution of Arabic Lexical Ambiguities with Transduction on Text Automaton 基于文本自动机的转导解译阿拉伯语词汇歧义研究
Nadia Ghezaiel, K. Haddar
{"title":"Toward the Resolution of Arabic Lexical Ambiguities with Transduction on Text Automaton","authors":"Nadia Ghezaiel, K. Haddar","doi":"10.1109/ACLING.2015.12","DOIUrl":"https://doi.org/10.1109/ACLING.2015.12","url":null,"abstract":"Lexical analysis can be a way to remove ambiguities in Arabic language. So their resolution is an important task in several Natural Language Processing (NLP) applications. In this context that this paper is inscribed. Our proposed resolution method is based essentially on the use of transducers on text automata. Indeed these transducers specify the lexical and contextual rules for Arabic language. They allow the resolution of lexical ambiguities. In order to achieve this resolution method, different types of lexical ambiguities are identified and studied to extract an appropriate set of rules. After that, we described lexical rules in ELAG [19] system (Elimination of Lexical Ambiguities by Grammars), which can delete paths representing morphosyntactic ambiguities. In addition, we present an experimentation implemented in the Unitex platform and conducted by various linguistic resources to obtain disambiguated syntactic structures suitable for the syntactic analysis. The obtained results are ambitious and can be improved by adding other rules and heuristics.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123930325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Unsupervised Data Driven Taxonomy Learning 无监督数据驱动分类法学习
Mahmoud M. Hosny, S. El-Beltagy, M.E. Allam
{"title":"Unsupervised Data Driven Taxonomy Learning","authors":"Mahmoud M. Hosny, S. El-Beltagy, M.E. Allam","doi":"10.1109/ACLING.2015.8","DOIUrl":"https://doi.org/10.1109/ACLING.2015.8","url":null,"abstract":"The ability to effectively organize textual information is a big challenge in intelligent text processing. With the increase in the amount of textual data being generated, this task is becoming more and more essential. In this paper we present an unsupervised computer-aided tool for automatically building classification schemes and taxonomies for enhancing the process of automated text classification. The tool utilizes the Wikipedia knowledge base and its categorization system to achieve its goal. Validation of the tool was done using a subset of a large language dataset obtained from the Google moderator series (Egypt 2.0) idea bank. The output of the tool was evaluated by comparing the similarity between the results obtained automatically from the tool, and those manually annotated by three different human evaluators, verifying the effectiveness of the tool. The tool showed effectiveness with a precision of 88.6% and recall of 81.2%.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131719814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Which Configuration Works Best? An Experimental Study on Supervised Arabic Twitter Sentiment Analysis 哪种配置效果最好?监督阿拉伯语推特情感分析的实验研究
Talaat Khalil, Amal Halaby, Muhammad Hammad, S. El-Beltagy
{"title":"Which Configuration Works Best? An Experimental Study on Supervised Arabic Twitter Sentiment Analysis","authors":"Talaat Khalil, Amal Halaby, Muhammad Hammad, S. El-Beltagy","doi":"10.1109/ACLING.2015.19","DOIUrl":"https://doi.org/10.1109/ACLING.2015.19","url":null,"abstract":"Arabic Twitter Sentiment Analysis has been gaining a lot of attention lately with supervised approaches being exploited widely. However, to date, there has not been an experimental study that examines how different configurations of the Bag of Words model, text representation scheme, can affect various supervised machine learning methods. The goal of the presented work is to do exactly that. Specifically, this work examines which configurations work best for each of three machine learning approaches that have shown good results when applied on the task of sentiment analysis, namely: Support Vector Machines, Compliment Naïve Bayes, and Multinomial Naïve Bayes. Experimenting with different datasets has shown that each of these classifiers has a Bag of Words configuration in conjunction with which, it consistently performs best. It also showed that some features are dataset dependent.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114365654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 17
Transducers Cascades for an Automatic Recognition of Arabic Named Entities in Order to Establish Links to Free Resources 转换器级联自动识别阿拉伯语命名实体,以建立链接到免费资源
Fatma Ben Mesmia, Nathalie Friburger, K. Haddar, D. Maurel
{"title":"Transducers Cascades for an Automatic Recognition of Arabic Named Entities in Order to Establish Links to Free Resources","authors":"Fatma Ben Mesmia, Nathalie Friburger, K. Haddar, D. Maurel","doi":"10.1109/ACLING.2015.16","DOIUrl":"https://doi.org/10.1109/ACLING.2015.16","url":null,"abstract":"Arabic named entities (ANE) are often sources of information. That is why they are used by several applications of natural language processing (NLP) mainly in information retrieval. In order to improve the relevance of the information obtained, links to free resources can be established. Indeed, the recognition of these entities requires the use of adequate formalisms. In this paper, we propose an approach based on transducer cascades which allows the recognition of ANE more precisely the dates. This categorycan be an integral part in the events and the names of places. The implementation of the developed transducers cascades elaborated by using the CasSys tool is available under the Unitex platform. The results are motivating.","PeriodicalId":404268,"journal":{"name":"2015 First International Conference on Arabic Computational Linguistics (ACLing)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122008817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信