Knowledge bases such as Freebase, YAGO, DBPedia, and Nell contain a number of facts with various entities and relations. Since they store many facts, they are regarded as core resources for many natural language processing tasks. Nevertheless, they are not normally complete and have many missing facts. Such missing facts keep them from being used in diverse applications in spite of their usefulness. Therefore, it is significant to complete knowledge bases. Knowledge graph embedding is one of the promising approaches to completing a knowledge base and thus many variants of knowledge graph embedding have been proposed. It maps all entities and relations in knowledge base onto a low dimensional vector space. Then, candidate facts that are plausible in the space are determined as missing facts. However, any single knowledge graph embedding is insufficient to complete a knowledge base. As a solution to this problem, this paper defines knowledge base completion as a ranking task and proposes a committee-based knowledge graph embedding model for improving the performance of knowledge base completion. Since each knowledge graph embedding has its own idiosyncrasy, we make up a committee of various knowledge graph embeddings to reflect various perspectives. After ranking all candidate facts according to their plausibility computed by the committee, the top-k facts are chosen as missing facts. Our experimental results on two data sets show that the proposed model achieves higher performance than any single knowledge graph embedding and shows robust performances regardless of k. These results prove that the proposed model considers various perspectives in measuring the plausibility of candidate facts.
Lignin is a complex polymer that is embedded in plant cell walls to provide physical support and water protection. For these reasons, the production of lignin is closely linked with plant adaptation to terrestrial regions. In response to developmental cues and external environmental conditions, plants use an elaborate regulatory network to determine the timing and location of lignin biosynthesis. In this review, we summarize the canonical lignin biosynthetic pathway and transcriptional regulatory network of lignin biosynthesis, consisting of NAC and MYB transcription factors, to explain how plants regulate lignin deposition under drought stress. Moreover, we discuss how the transcriptional network can be applied to the development of drought tolerant plants.
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