A New Alignment Word-Space Approach for Measuring Semantic Similarity for Arabic Text

This work presents a new alignment word-space approach for measuring the similarity between two snipped texts. The combines measurement methods: alignment-based and vector space-based. space-based method depends on semantic net that represents meaning of words as vectors. These vectors are lemmatized to enrich search space. generates an word space matrix (AWSM) texts according generated spaces. Finally, degree sentence is measured using some proposed rules. Four experiments were carried out evaluate performance approach, different datasets. experimental results proved applying lemmatization process input text model has better effect. correctness reaches 0.7212 which considered one best published Arabic similarities.