Yen-Kuan Lee

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In this paper, we introduce the concept of a novel application, called Knowledge Learning from User Search, aiming at identifying timely new knowledge triples from user search log. In the literature, the need of knowledge enrichment has been recognized as the key to the success of knowledge-based search. However, previous work of automatic knowledge(More)
In this paper, we explore a novel problem to identify timely new knowledge triples. In the literature, the need of knowledge enrichment has been recognized as the key to the success of semantic search. However, previous work of automatic knowledge extraction, such as Google Knowledge Vault, aim at identifying the unannotated knowledge triples from the full(More)
In this paper, we explore a novel framework to generate a well-known text cloud visualization with the conceptual sense. The traditional text cloud is usually generated according to the word occurrence, possibly including the idf-based concept for word weight. The solution is applicable for the long articles. However, for a set of short sentences such as(More)
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