Oct 13, 2019 · Given a short-text as input, we map each term to the corresponding candidate concepts defined in lexical knowledge base (e.g., Probase), and ...
The experimental results show that our method achieves higher accuracy and efficiency in short-text conceptualiza- tion than the state-of-the-art algorithms.
This paper proposes a novel framework based on both statistic information and semantic information, for co-ranking terms and their corresponding concepts ...
Short-Text Conceptualization Based on a Co-ranking Framework via Lexical Knowledge Base. October 2019; Lecture Notes in Computer Science. DOI:10.1007/978-3-030 ...
Short-Text Conceptualization Based on a Co-ranking Framework via Lexical Knowledge Base · Yashen Wang. Computer Science. CCL. 2019. TLDR. This paper proposes a ...
In this paper, we propose a probabilistic framework, which includes a knowledgebase and certain inferencing techniques on top of the knowledgebase, to enable ...
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Thus an ideal co-ranking framework is introduced to address the problem of short text conceptualization. After co-ranking the words and the corresponding ...
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This book constitutes the proceedings of the 18th China National Conference on Computational Linguistics, CCL 2019, held in Kunming, China, in October 2019.
Huang et al. introduce a coranking framework to extract contextual keywords and combine the keywords with the attention-based strategy for short-text embedding ...
By leveraging a large taxonomy knowledgebase, it learns a concept model for each category, and conceptualizes a short text to a set of relevant concepts. A ...
Missing: Lexical | Show results with:Lexical