A Framework of Hybrid Semantic Speech Query via Stemmer for Quran Documents Results

The single query has a lack of words reference to provide more related words for documents result retrieval. The study covers those available words in the dictionary which related to the single word. Therefore it also means that single word is assigned for many words from single query as multi-relevant queries in the dictionary. Hence, the single query is speech query to be converted to words in the query. Cross language information retrieval (CLIR) system investigates the Quran system results performance using looping referred semantic words and stemmers are known as stemming looping semantic query (SLSQ). The query however is based on the speech to be input and converted into text. Therefore, this study is conducted with the purpose to introduce the framework which covers speech, semantic and stemmers approach against the queries and vice versa. Furthermore, it is also conducted to investigate the performance SLSQ based on total retrieve and relevant to maximize words than single word. It also found that looping semantic words technique in dictionary contributes to better approach in using looping referred words in the dictionary for its better performance for Quran document results.