Arabic Information Retrieval
نویسندگان
چکیده
In the past several years, Arabic Information Retrieval (IR) has garnered significant attention. The main research interests have focused on retrieval of formal language, mostly in the news domain, with ad hoc retrieval, OCR document retrieval, and cross-language retrieval. The literature on other aspects of retrieval continues to be sparse or non-existent, though some of these aspects have been investigated by industry. Others aspects of Arabic retrieval that have received attention include document image retrieval, speech search, social media and web search, and filtering. However, efforts on different aspects of Arabic retrieval continue to be deficient and severely lacking behind efforts in other languages. The survey covers: 1) general properties of the Arabic language; 2) some of the aspects of Arabic that affect retrieval; 3) Arabic processing necessary for effective Arabic retrieval; 4) Arabic retrieval in public IR evaluations; 5) specialized retrieval problems, namely Arabic-English CLIR, Arabic Document Image Retrieval, Arabic Social Search, Arabic Web Search, Question Answering, Image retrieval, and Arabic Speech Search; 6) Arabic IR and NLP resources; and 7) open IR problems that require further attention. K. Darwish and W. Magdy. Arabic Information Retrieval. Foundations and Trends © in Information Retrieval, vol. 7, no. 4, pp. 239–342, 2013. DOI: 10.1561/1500000031.
منابع مشابه
Building an Arabic Stemmer for Information Retrieval
In TREC 2002 the Berkeley group participated only in the English-Arabic cross-language retrieval (CLIR) track. One Arabic monolingual run and three English-Arabic cross-language runs were submitted. Our approach to the crosslanguage retrieval was to translate the English topics into Arabic using online English-Arabic machine translation systems. The four official runs are named as BKYMON, BKYCL...
متن کاملTowards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing
Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval in particular. Hence, Arabic cannot trust any web information retrieval system as reliable and relevant as Google search engine. In this context, we dared to focus all our researches to implemen...
متن کاملTowards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing
Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval in particular. Hence, Arabic cannot trust any web information retrieval system as reliable and relevant as Google search engine. In this context, we dared to focus all our researches to implemen...
متن کاملTowards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing
Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval in particular. Hence, Arabic cannot trust any web information retrieval system as reliable and relevant as Google search engine. In this context, we dared to focus all our researches to implemen...
متن کاملTowards an Arabic Web-based Information Retrieval System (ARABIRS): Stemming to Indexing
Arabic, the mother tongue of over 300 million people around the world, is known as one of the most difficult languages in Automatic Natural Language processing (NLP) in general and information retrieval in particular. Hence, Arabic cannot trust any web information retrieval system as reliable and relevant as Google search engine. In this context, we dared to focus all our researches to implemen...
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ورودعنوان ژورنال:
- Foundations and Trends in Information Retrieval
دوره 7 شماره
صفحات -
تاریخ انتشار 2014