This paper proposes a hybrid model to address the task of sense guessing for Chinese unknown words. Three types of similarity, i.e., positional, syntactic and semantic similarity, are analyzed; and three models are developed accordingly. Then the three models are combined to form a hybrid one (HPPS Model). To verify the effectiveness and consistency of HPPS, experiments were conducted on ten te...

Accuracy of predicting the user preference score is the most important element of collaborative filtering. This paper proposes novel similarity measures using difference score entropy of common rating items between two users. The proposed similarity measures can apply various weights according to the score difference, to evaluate the similarity. We implemented a recommender system using the pro...

This paper proposes an image retrieval method based on multi-feature similarity score fusion using genetic algorithm. Single feature describes image content only from one point of view, which has a certain one-sided. Fusing multifeature similarity score is expected to improve the system's retrieval performance. In this paper, the retrieval results from color feature and texture feature are anal...

This paper proposes an image retrieval method based on multi-feature similarity score fusion using genetic Algorithm. Single feature describes image content only from one point of view and Fusing Multifeature similarity score is expected to improve the system's retrieval performance. In this paper, the retrieval results from color feature and texture feature are analyzed, and the method of fusi...

Interpretable semantic textual similarity (iSTS) task adds a crucial explanatory layer to pairwise sentence similarity. We address various components of this task: chunk level semantic alignment along with assignment of similarity type and score for aligned chunks with a novel system presented in this paper. We propose an algorithm, iMATCH, for the alignment of multiple non-contiguous chunks ba...