Arabic user search Query correction and expansion

American Journal of Applied Sciences, 2013

The word mismatch problem is fundamental to Information retrieval. Query expansion process helps to overcome this problem. Based on the Arabic corpuses, the comparisons between two query expansion techniques (global and local query) have been conducted to determine the query effectiveness. First one represents the local context analysis which represents a local method, while a global method was the second technique that has been represented by the Association and similarity thesauruses. These techniques can be used in any special field or domain to improve the expansion process and to get more relevant documents for the user's query. This study introduces a comparison between these approaches and shows their effectiveness. Although, local context analysis has some advantages over the similarity thesaurus, Association thesaurus which is global is generally the most effective one.

IRAQI JOURNAL OF SCIENCE, 2017

Query expansion (QE) is a successful idea to overcome the weaknesses in the information retrieval performance. The QE requires finding out appropriate word synonyms of the query words in a process that can be made automatically without any user intervention. The candidate synonyms should be associated with an accurate meaning (sense) of the original word. Arabic language is rich in multiple meanings and this requires using the so-called word sense disambiguation (WSD). WSD in general is a task to discover the correct sense of a word within context. To disambiguate the word sense, three different traditional semantic measures are tested in this work; they are called lch, wup, and path respectively. The proposed system uses these measures along with an automatic synonym selection method employed to expand the query. The proposed system outperforms the traditional baseline system that has no query expansion technique in a rate from 10% to 18 % and reduces the latency in an approximate rate from 0.232 to 0.283 second for each query.

This paper presents an attempt to show the efficiency of some search engines in handling Arabic keywords. To achieve this, a comparison was made among the number of retrieved pages, retrieving time, and stability (in both the number of retrieved pages and the order for each retrieved page) for each of the 20 Arabic keywords selected (with its roots) after being simultaneously entered to the selected four search engines. Search engines tested in this experiment were Google, Yahoo, Al-hoodhood and Ayna. Google was the best search engine among the four selected search engines according to the results obtained over 10 weeks of experimenting.

Journal of Information Science Theory and Practice, 2020

Information need has been one of the main motivations for a person using a search engine. Queries can represent very different information needs. Ironically, a query can be a poor representation of the information need because the user can find it difficult to express the information need. Query Expansion (QE) is being popularly used to address this limitation. While QE can be considered as a language-independent technique, recent findings have shown that in certain cases, language plays an important role. Arabic is a language with a particularly large vocabulary rich in words with synonymous shades of meaning and has high morphological complexity. This paper, therefore, provides a review on QE for Arabic information retrieval, the intention being to identify the recent state-of-the-art of this burgeoning area. In this review, we primarily discuss statistical QE approaches that include document analysis, search, browse log analyses, and web knowledge analyses, in addition to the sem...

2016

This paper reports the results of investigating the impact of query length on the performance of Arabic retrieval. Thirty queries were used in the investigation, each of which was phrased in three different types of length: short, medium, and longer, giving ninety different queries. A Corpus of one thousand documents on herbal medication was used and expert judgments were used to determine document relevance to each query. The main finding of this research is that using shorter queries improves both precision and recall. Due to the absence of other results to compare with and the lack of agreement on how length affects retrieval, it has been concluded that the results should be viewed in light of the type of dataset used and how queries were formulated and categorized.

Albeit real progress has been made during the last two decades, finding or retrieving information in Arabic with the help of a search engine remains difficult, owing to the high level of ambiguity entailed by the structure of 'unvowelled' Arabic writing. These language-specific difficulties are brought to a peak in the case of queries based on single words. The contribution analyses the results of search queries on Google, which are compared to the results of word-form analyses obtained both on the ArabiCorpus site (http://arabicorpus.byu.edu/) and with analysers based on the DIINAR.1 lexical resource (references at http://diinar.univ-lyon2.fr). An assessment protocol is proposed. Clearly, it aims at evaluating neither the analysers of ArabiCorpus and DIINAR.1, nor the Google search engine. Examining the latter is quite another question, related to Google ranking, and speed. The aim of the paper, instead, is to explore and assess the possibilities and limitations of word-form based queries in Arabic, i.e. the result of queries obtained with wordform based analysers and language resources (what can be obtained and what strictly speaking cannot). The protocol includes (a) comparing results obtained through Google with the often numerous word-forms obtained through the two other sources, (b) considering a number of semantic aspects related to the contexts query words appear in, and (c) taking into account wordbefore/word-after collocations and set phrases. It eventually introduces essential features of a new type of lexical resource for future Arabic search engines, which needs to contain, among other components : (a) a compact and comprehensive database operating at word-form level, such as DIINAR.1, and (b) an extended lexical resource that includes semantic relations, collocations and set or semiset expressions.

2004

Human Language Technology has played a big role in implementing Latin based information retrieval systems. Two of the most sited techniques are stemming and truncation. Numerous studies have showed that the inflectional structure of words has a big impact on the retrieval accuracy of Latin-based languages information retrieval systems (IRS). Stemming or truncation is done for two principal reasons: the reduction in index storage required and the increase in performance due to the use of word variants. Several stemming algorithms were proposed for stemming text such as Porter for English.

2018

Information retrieval aims to find all relevant documents responding to a query from textual data. A goodinformation retrieval system should retrieve only those documents that satisfy the user query. Although several models weredeveloped, most of Arabic information retrieval models do not satisfy the user needs. This is because the Arabic language ismore powerful and has complex morphology as well as high polysemy. This paper first investigates the most recent Arabicinformation retrieval model and then presents two different approaches to enhance the effectiveness of the adopted model.The main idea of the proposed approaches is to modify and/or expand the user query. The first approach expands user queryby using semantics of words according to an Arabic dictionary. The second approach modifies and/or expands user query byadding some useful information from the pseudo relevance feedback. In other words, the query is modified by selectingrelevant textual keywords for expanding the que...

2000

This paper addresses some issues involved in utilization of different levels of Arabic morphological knowledge in improving the search process in a search engine. The different levels of morphological knowledge can be considered as an incremental process considering the next sensitive word pattern in the context of enhancing the possibility of covering a higher recall and precision.

Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP), 2014

Traditional keyword based search is found to have some limitations. Such as word sense ambiguity, and the query intent ambiguity which can hurt the precision. Semantic search uses the contextual meaning of terms in addition to the semantic matching techniques in order to overcome these limitations. This paper introduces a query expansion approach using an ontology built from Wikipedia pages in addition to other thesaurus to improve search accuracy for Arabic language. Our approach outperformed the traditional keyword based approach in terms of both F-score and NDCG measures.