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Similarity between different short texts can be computed and the similarity output is a real value within 0 to 1. The higher the value, the better the similarity. This similarity value can be directly used for ranking results as well as more complex systems as a one-dimension basic featureFree Trial
Based on multiple computing models, such as the traditional one and the deep learning one, as well as mass training data, similarity between different short texts is computed and the similarity output is a real value within 0 to 1. The higher the value, the better the similarity
It is applicable for Text Categorization, assisting pre-categorizing search; it can recommend products with similar titles according to customer’s browsing records; it can categorize answers and questions, etc.
With Vertical Categorization, similar texts can be retrieved according to texts and pre-categorizing search can be assisted
With Product Recommendation, products with similar titles can be detected according to product titles browsed by the customer and recommended to users
With Question and Answer Classification, similar questions and answers can be searched for users