English-Persian Tezt Retrieval Using Concept Graph
Cross-language information retrieval (CLIR) is the retrieval process where the user presents queries in one language to retrieve documents in another language. In this field the resolution of lexical ambiguity in translating queries is a key challenge. In this paper, we propose a technique for calculating translation probabilities based on creating query terms concept graphs for selecting the right translation sense of query terms for English-Persian text retrieval. We present an efficient statistical method for creating this graph. We test the effectiveness of the proposed disambiguation method on Hamshahri collection1 that is standardized according to CLEF standards. Evaluation using this data collection shows great effectiveness of the proposed method.
Tezt retrieval Concept graph Term Weighting Translation disambiguation
Farnaz Teymoorian Mehran Mohsenzadeh MirAli Seyyedi
Department of Computer Engineering Islamic Azad University - North Tehran Branch, Tehran, Iran Department of Computer Engineering Islamic Azad University - Science & Research Center, Tehran, Iran Department of Computer Engineering Islamic Azad University - South Tehran Branch, Tehran, Iran
国际会议
北京
英文
2395-2399
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）