DCRL-KG: Distributed Multi-Modal Knowledge Graph Retrieval Platform Based on Collaborative Representation Learning

The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,which accounts for the advantage of the multi-modal knowledge graph.In the field of cross-modal retrieval platforms,multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational infor-mation provided by knowledge graphs.The representation learning method is sig-nificant to the application of multi-modal knowledge graphs.This paper proposes a distributed collaborative vector retrieval platform(DCRL-KG)using the multi-modal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval.Firstly,use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency.Secondly,this paper uses BabelNet to expand the knowledge graph through multi-ple filtering processes and increase the diversification of information.Finally,this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval.The paper uses sentence retrieval and image retrieval experi-ments to prove that the platform can optimize the storage structure of the multi-modal knowledge graph and have good performance in multi-modal space.

X-RESTORE: Middleware for XML's Relational Storage and Retrieve

We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have de monstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. Our approach is also flexible enough to support X ML documents both with Schema and without Schema, and applications both retrieva l and update. We also present the architecture of middleware for application acc essing XML documents stored in relations, and an algorithm translating a given X ML document into relations effectively.

Semantic web-based networked manufacturing knowledge retrieval system

To deal with a lack of semantic interoperability of traditional knowledge retrieval approaches, a semantic-based networked manufacturing （NM） knowledge retrieval architecture is proposed, which offers a series of tools for supporting the sharing of knowledge and promoting NM collaboration. A 5-tuple based semantic information retrieval model is proposed, which includes the interoperation on the semantic layer, and a test process is given for this model. The recall ratio and the precision ratio of manufacturing knowledge retrieval are proved to be greatly improved by evaluation. Thus, a practical and reliable approach based on the semantic web is provided for solving the correlated concrete problems in regional networked manufacturing.

Travel time and alternative configurations analysis for automated storage/retrieval systems based on geometrical method

In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.

Product-design knowledge retrieval based on ontology

In order to improve the utilization ratio of knowledge retrieval, a product-design knowledge retrieval approach based on ontology is proposed. A representation model of product-design knowledge is proposed according to its characteristics. Domain ontology of product-design is estab- lished and the semantic annotation technology is used to connect the design knowledge and ontolo- gy. A new semantic annotation format is developed and semantic information of the design knowl- edge is enriched by making use of ontology. On that basis a retrieval algorithm is designed for semantic retrieval. Finally, this approach is used in a knowledge management system for military-vehi- cle design and its effectiveness and feasibility are validated. Results show that the recall ratio and the precision ratio of knowledge retrieval are improved greatly and users＇ requirements in semantic retrieval are satisfied.

The Cloud Storage Ciphertext Retrieval Scheme Based on ORAM

Due to its characteristics distribution and virtualization, cloud storage also brings new security problems. User＇s data is stored in the cloud, which separated the ownership from management. How to ensure the security of cloud data, how to increase data availability and how to improve user privacy perception are the key issues of cloud storage research, especially when the cloud service provider is not completely trusted. In this paper, a cloud storage ciphertext retrieval scheme based on AES and homomorphic encryption is presented. This ciphertext retrieval scheme will not only conceal the user retrieval information, but also prevent the cloud from obtaining user access pattern such as read-write mode, and access frequency, thereby ensuring the safety of the ciphertext retrieval and user privacy. The results of simulation analysis show that the performance of this ciphertext retrieval scheme requires less overhead than other schemes on the same security level.

A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

Ontology Based Ocean Knowledge Representation for Semantic Information Retrieval

The drastic growth of coastal observation sensors results in copious data that provide weather information.The intricacies in sensor-generated big data are heterogeneity and interpretation,driving high-end Information Retrieval(IR)systems.The Semantic Web(SW)can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval.This paper focuses on exploiting the SWbase systemto provide interoperability through ontologies by combining the data concepts with ontology classes.This paper presents a 4-phase weather data model:data processing,ontology creation,SW processing,and query engine.The developed Oceanographic Weather Ontology helps to enhance data analysis,discovery,IR,and decision making.In addition to that,it also evaluates the developed ontology with other state-of-the-art ontologies.The proposed ontology’s quality has improved by 39.28%in terms of completeness,and structural complexity has decreased by 45.29%,11%and 37.7%in Precision and Accuracy.Indian Meteorological Satellite INSAT-3D’s ocean data is a typical example of testing the proposed model.The experimental result shows the effectiveness of the proposed data model and its advantages in machine understanding and IR.

IOTA-Based Data Encryption Storage and Retrieval Method

At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not supporting private data storage,large data operation costs,and not supporting Data field query.This paper proposes a method of data encryption storage and retrieval based on the IOTA distributed ledger,combined with the fast transaction processing speed and zero-value transactions of the IOTA blockchain,through the Masked Authenticated Messaging technology,so that the data is encrypted in the data stream.The form is stored in the distributed ledger,quickly retrieved through the field index mechanism established by the data form,and the data operation is carried out on the chain.Experimental results show that this system has high storage,encryption and retrieval performance,and good practicability.

ISI Web of Knowledge集成检索平台评析

本文从资源整合与集成检索的角度出发,对 ISI Web of KnowledgeSM 平台的集成化信息检索机制作了一个全面的解析;同时指出其优势与不足之处,希望为我国图书情报机构打造成熟的、满足用户方便、快捷获取所需信息的检索平台提供一点借鉴。

ISI Web of Knowledge跨库检索功能与操作技巧

ISI Web of Knowledge是新一代的学术信息资源整合体系,是Web of science的最新升级平台。 本文主要介绍了这一体系的跨库检索功能及其操作技巧。

On-Demand Photon Storage and Retrieval with a Solid-State Photon Molecule at Room Temperature

Deterministically achieving on-chip photon storage and retrieval is a fundamental challenge for integrated photonics.Moreover,this requirement is increasingly urgent as photon storage and retrieval is crucial to realize truly scalable room-temperature quantum computing.However,most of existing quantum memories integrated on chips must either work at cryogenic temperature or else are strongly coupled with the environment,which hugely reduces the efficiency.Here,we propose an on-chip room-temperature quantum memory comprising three coupled microcavities,which presents an ideal dark state decoupled by a waveguide,thereby allowing on-demand photon storage and retrieval with high efficiency and high fidelity simultaneously.Furthermore,we demonstrate that the single-photon temporal duration can be increased or decreased by a factor of 10^(3),thereby enabling many crucial quantum applications.Our error-robust approach highlights the potential for a solid-state photonic molecule for use as on-chip quantum memory and for optical quantum computing.

Sand Storage, Extending the Shelf-Life of Fresh Sweetpotato Roots for Home Consumption and Market Sales

Uni-modal rainfall pattern has long dry spell wherein sweetpotato is scarce, expensive but cheap at harvest. The crop is mostly consumed, processed or sold. Extending shelf-life of roots is crucial for Malawi and Northern Ghana as the crop has high value. Trials were conducted in the countries at the community level. In the dry season, temperature is cool in Malawi while warm in Ghana, but thru harmattan, the night is cool with low relative humidity. In Malawi, orange-fleshed sweetpotato Zondeni var., white and yellow types were assessed in three types of storage, Afghan ventilated pit store, storage in dry sand of pit-steps, and of a granary In Ghana, local moistened heap and sandbox were compared. In Malawi, weight losses were calculated relative to the quantity stored at start, it was not cumulative. At 1.5 months no significant difference was among treatments. By 3.5 months the pit-steps method emerged to be superior and continued to 6.5 months. Losses in granary were due to shriveling, in the pit-stepsdue to termites and rats, and in ventilated pit due to termites, rats and Java black rot. Sprouting was high in pit-steps, but it was simply removed and roots returned to storage. At 6.5 months, the beta-carotene of Zondeni roots was traceable. Farmers gained high price when selling them as roots were scarce. Women favored the pit-steps because it was manageable. In Ghana, the sandbox was superior to local moistened heap. Methods designed were suitable for home consumption, but will require modification for commercialization.

A dynamic knowledge base based search engine

Search engines have greatly helped us to find the desired information from the Internet. Most search engines use keywords matching technique. This paper discusses a Dynamic Knowledge Base based Search Engine （DKBSE）, which can expand the user＇s query using the keywords＇ concept or meaning. To do this, the DKBSE needs to construct and maintain the knowledge base dynamically via the system＇s searching results and the user＇s feedback information. The DKBSE expands the user＇s initial query using the knowledge base, and returns the searched information after the expanded query.

知识图谱技术实现流程及相关应用

目前,人类已经迈入信息时代的大门,大数据技术得到广泛化应用,信息数据成为一项宝贵的资源,通过知识图谱可以对海量数据进行整合、利用,挖掘高价值信息,以便为决策制定等多方面提供重要支持。基于此,该文围绕知识图谱的技术实现及相关应用展开深入、全面的探析。

面向医药卫生知识服务系统的学术知识图谱构建与应用研究

目的/意义探析知识服务系统中学术知识图谱的构建框架和方法,为开展基于科技大数据的新型知识服务提供参考。方法/过程提出面向知识服务系统的学术知识图谱构建框架及方案,以医药卫生知识服务系统为例,详细阐述构建步骤及构建过程中的关键技术。结果/结论基于多类型科技数据资源构建的学术知识图谱有助于更好地开展学术实体的关联挖掘与知识推理,提高科技数据组织管理效率,提供更高效的知识服务。

基于知识图谱的存储系统单元教学设计

针对存储系统教学单元概念复杂、术语众多以及理解难度大等特点,提出一种基于知识图谱的教学设计方法。该方法通过知识图谱将碎片化的知识点体系化、可视化,从教学内容分析、知识图谱构建、重难点分析及对策设计、教学策略设计、教学过程设计和过程性考核设计等多个环节进行教学设计,并融入思政元素、职业素养,促进“德法知技”综合育人。

融合知识推理与相似度检索的民众诉求大模型构建与应用

高效回复民众诉求是实现智能化管理、提升民众满意度的必要措施,将智能问答应用于民众诉求能有效节约人力和时间资源。然而,智能问答中基于规则和检索的模型依赖预设知识,当诉求超出预设知识范围时无法提供有效回复,在处理多轮对话时也无法保持对话连贯性。现有的大语言模型可以和用户流畅对话,但通用大语言模型缺乏诉求领域知识。由于训练数据中问答对的信息没有覆盖回答用户问题所需要的知识,导致通用大语言模型生成错误回复或答非所问,产生幻觉。针对上述问题,构建了面向民众诉求领域的智能问答大语言模型(PC-LLM)。设计基于BERT-BiLSTM-CRF的实体关系抽取模型获得诉求工单中实体及其关系,进而构建诉求知识图谱,使用BERT模型对诉求工单向量化并构建诉求工单向量索引库;回复生成阶段,抽取用户诉求的实体和关系,在诉求知识图谱中通过实体链接进行知识推理,获取潜在关系提示,同时在诉求工单向量索引库内对诉求进行快速检索,获取相似诉求并构建相似诉求提示;将潜在关系提示、相似诉求提示与用户诉求融合形成综合提示,引导大语言模型生成准确的回复。实验分析显示,该大语言模型在诉求数据集中的表现明显优于ChatGPT4o、文心一言、通义千问等大语言模型。

知识图谱特征重构下无线传感网络数据存储恢复

为了提升无线传感网络数据存储恢复成功率,保障无线传感网络数据存储安全性,提出知识图谱特征重构下无线传感网络数据存储恢复方法。通过基于知识图谱的特征重构方法优化数据存储结构;利用BP神经网络和LEACH算法,对特征重构后的数据进行融合。最后,结合多级网络编码和纠删码的原理,构建多级编码矩阵对融合数据进行多级编码,并生成多份数据副本进行存储,实现无线传感网络数据存储恢复。实验结果表明,该方法能够提升数据存储恢复成功率至90%以上,通信代价低于1.5×10^(5) Mbit/s,存储恢复时间低于0.7 ms,可以在提升恢复成功率的同时,降低存储通信代价和存储恢复时间。

基于CiteSpace的相变储能材料研究热点可视化分析

【目的】分析国内相变储能材料的研究趋势、研究方向和研究内容。【方法】利用CiteSpace软件对1996—2022年CNKI收录的400篇核心期刊论文进行分析研究。【结果】文献发表量呈现出阶段性增加的趋势,从2014年开始,相变储能材料的研究出现了快速增长,说明相变储能材料的研究已成为国内研究热点;研究文献主要分为8个聚类单元,分别为0#相变材料、1#石蜡、2#相变、3#相分离、4#脂肪酸、5#应用、6#相变储能、7#储热。【结论】直观地展示了相变储能材料的研究现状、研究热点,并对研究内容进行了梳理和总结,可为相变储能材料的相关研究提供参考。