Showing results for Ranking Entity Based on Both of Word Frequency and Word Semantic Features.
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Aug 3, 2016 · Abstract:Entity search is a new application meeting either precise or vague requirements from the search engines users.
A series of similarity features based on both of the word frequency features and the word semantic features are proposed and described and the ranking ...
The common method is to extract the features for each of the input text pair and then rank them on the various similarity measures based on the lexical and ...
... word frequency features and the word semantic features and describe our ranking architecture and experiment details. Duke Scholars. Kaizhu Huang. Author ...
Entity search is a new application meeting either precise or vaguerequirements from the search engines users. Baidu Cup 2016 Challenge justprovided such a ...
Missing: Semantic | Show results with:Semantic
Jan 24, 2019 · Another way to use knowledge graphs in document-ranking is the word-entity duet framework, which represents queries and documents using both ...
Then, this paper enhances two entity-based models—toy model and Explicit Semantic Ranking model (ESR)—by considering the importance of entities. In contrast to ...
Jan 17, 2019 · Then, this paper enhances two entity-based models—toy model and Explicit Semantic Ranking model (ESR)—by considering the importance of entities.
Feb 18, 2021 · A similar approach is [11] that describes a learning to rank approach where the training is based both on Bag- of-Words (BoW) and BoE features.
different sequences of relationships that interconnect two entities; semantic associations are based on intuitive notions such as connectivity and semantic ...