In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shippi...In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.展开更多
网构软件代表了Internet环境下的一种新型的软件形态,但仍然面临着外部环境显式化、软件实体主体化、运行机制自适应等问题.从构件的角度出发,提出了EBDI(electronic business document exchange)结构以表示能够根据环境变化实施自主行...网构软件代表了Internet环境下的一种新型的软件形态,但仍然面临着外部环境显式化、软件实体主体化、运行机制自适应等问题.从构件的角度出发,提出了EBDI(electronic business document exchange)结构以表示能够根据环境变化实施自主行为的构件,利用动态绑定关系解释了构件的自适应演化特征.根据形式化的Role模型,描述了构件的运行状态、自主运行及自适应演化运行机制开发了DAgent-Internetware原型作为网构软件的支撑平台,支持以DAgent为构件的网构软件从设计到实现、部署、运行、演化等一系列流程.展开更多
Document collections do not only contain rich semantic content but also a diverse range of relationships.We propose WordleNet,an approach to supporting effective relationship exploration in document collections.Existi...Document collections do not only contain rich semantic content but also a diverse range of relationships.We propose WordleNet,an approach to supporting effective relationship exploration in document collections.Existing approaches mainly focus on semantic similarity or a single category of relationships.By constructing a general definition of document relationships,our approach enables the flexible and real-time generation of document relationships that may not otherwise occur to human researchers and may give rise to interesting patterns among documents.Multiple novel visual components are integrated in our approach,the effectiveness of which has been verified through a case study,a comparative study,and an eye-tracking experiment.展开更多
文摘In the international shipping industry, digital intelligence transformation has become essential, with both governments and enterprises actively working to integrate diverse datasets. The domain of maritime and shipping is characterized by a vast array of document types, filled with complex, large-scale, and often chaotic knowledge and relationships. Effectively managing these documents is crucial for developing a Large Language Model (LLM) in the maritime domain, enabling practitioners to access and leverage valuable information. A Knowledge Graph (KG) offers a state-of-the-art solution for enhancing knowledge retrieval, providing more accurate responses and enabling context-aware reasoning. This paper presents a framework for utilizing maritime and shipping documents to construct a knowledge graph using GraphRAG, a hybrid tool combining graph-based retrieval and generation capabilities. The extraction of entities and relationships from these documents and the KG construction process are detailed. Furthermore, the KG is integrated with an LLM to develop a Q&A system, demonstrating that the system significantly improves answer accuracy compared to traditional LLMs. Additionally, the KG construction process is up to 50% faster than conventional LLM-based approaches, underscoring the efficiency of our method. This study provides a promising approach to digital intelligence in shipping, advancing knowledge accessibility and decision-making.
文摘网构软件代表了Internet环境下的一种新型的软件形态,但仍然面临着外部环境显式化、软件实体主体化、运行机制自适应等问题.从构件的角度出发,提出了EBDI(electronic business document exchange)结构以表示能够根据环境变化实施自主行为的构件,利用动态绑定关系解释了构件的自适应演化特征.根据形式化的Role模型,描述了构件的运行状态、自主运行及自适应演化运行机制开发了DAgent-Internetware原型作为网构软件的支撑平台,支持以DAgent为构件的网构软件从设计到实现、部署、运行、演化等一系列流程.
基金partially supported by the National Natural Science Foundation of China (Nos. 61602340 and 61572348)the National Key Research and Development Program of China (Nos. 2018YFC0831700 and 2018YFC0809800)
文摘Document collections do not only contain rich semantic content but also a diverse range of relationships.We propose WordleNet,an approach to supporting effective relationship exploration in document collections.Existing approaches mainly focus on semantic similarity or a single category of relationships.By constructing a general definition of document relationships,our approach enables the flexible and real-time generation of document relationships that may not otherwise occur to human researchers and may give rise to interesting patterns among documents.Multiple novel visual components are integrated in our approach,the effectiveness of which has been verified through a case study,a comparative study,and an eye-tracking experiment.
