Hybrid Query Expansion Model Based on Pseudo Relevance Feedback and Semantic Tree for Arabic IR

In this paper, the authors propose and readapt a new concept-based approach of query expansion in the context of Arabic information retrieval. The purpose is to represent the query by a set of weighted concepts in order to identify better the user's information need. Firstly, concepts are extracted from the initially retrieved documents by the Pseudo-Relevance Feedback method, and then they are integrated into a semantic weighted tree in order to detect more information contained in the related concepts connected by semantic relations to the primary concepts. The authors use the “Arabic WordNet” as a resource to extract, disambiguate concepts and build the semantic tree. Experimental results demonstrate that measure of MAP (Mean Average Precision) is about 10% of improvement using the open source Lucene as IR System on a collection formed from the Arabic BBC news.

RETRIEVAL PERFORMANCE OF ARABIC LIGHT STEMMERS

Despite the fact that stemming greatly improves Arabic information retrieval performance, yet no standard stemmer emerges in the field of Arabic IR due to some limitations and shortcomings. Among the recurring problems is that the stemmer can reduce unrelated words to the same stem as well as fall short to reduce related words to a common stem. Many studies have suggested Arabic algorithms to address the problem associated with stemming. This paper aims to review the state of the retrieval performance of Arabic Light stemmers based on the main objectives achieved, causes for retrieval success and failure, retrieval measure, the affixes, and methodologies. The results showed that light 10 has better retrieval performance compared to other reviewed Arabic light stemmers.

Enhanced Arabic Information Retrieval by Using Arabic Slang Language

Slang language has become the most used language in the most countries. It has almost become the first language in the social media, websites and daily conversations. Moreover, it has become used in many conferences to clarify information and to deliver the required purpose of them. Therefore, this great spread of slang language over the world. In Jordan indicates that it is important to know meanings of Jordanian slang vocabularies. Mainly, In research system, we created a system framework allows users to restore Arabic information depending on queries that are written in slang language and this framework was made basically by context-free grammar to convert from slang to classical and vice versa. In addition, to conclude with, we will apply it on the colloquial slang in North of Jordan specifically; Irbid, Ajloun, Jerash, Mafraq and AlRamtha city. As well as, we will make a special file for Non_Arabic words and the stop words too. After we made an evaluation for the system relying on the results of recall, precision and F-measure where the results of precision about 0.63 for both researches slang and classical query, and this indicates that the system supports searching in Jordanian slang language. The purpose of this research is to enhance Arabic information retrieval, and it will be a significant resource for researchers who are interested in slang languages. As well as, it helps tie communities together.