@inbook {27837,
	title = {Query Expansion Based-on Similarity of Terms for Improving Arabic Information Retrieval},
	booktitle = {Intelligent Information Processing VI},
	series = {IFIP Advances in Information and Communication Technology},
	volume = {385},
	year = {2012},
	note = {<p>n/a</p>
},
	pages = {167-176},
	publisher = {Springer},
	organization = {Springer},
	address = {Berlin Heidelberg},
	abstract = {<p> This research suggests a method for query expansion on Arabic Information Retrieval using Expectation Maximization (EM). We employ the EM algorithm in the process of selecting relevant terms for expanding the query and weeding out the non-related terms. We tested our algorithm on INFILE test collection of CLLEF2009, and the experiments show that query expansion that considers similarity of terms both improves precision and retrieves more relevant documents. The main finding of this research is that we can increase the recall while keeping the precision at the same level by this method. </p>
},
	keywords = {arabic, Arabic Information Retrieval, Arabic NLP, EM algorithm, Query Expansion},
	isbn = {978-3-642-32890-9},
	doi = {10.1007/978-3-642-32891-6_22},
	url = {http://dx.doi.org/10.1007/978-3-642-32891-6_22},
	attachments = {https://scholar.cu.edu.eg/sites/default/files/shaalan/files/query_arabic_iip_ifip.pdf},
	author = {Khaled Shaalan and Al-Sheikh, Sinan and Farhad Oroumchian},
	editor = {Shi, Zhongzhi and Leake, David and Vadera, Sunil}
}
