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About 5,866 papers for “dynamic knowledge base”
Shigeki Sugiyama · 2002
It is now possible to construct some sort of knowledge base by using neural networks. But this is, so called, a static knowledge base which cannot evolve itself for finding optimized answers which suit an initial aim if the initial answer does not satisfy the aim. So, in this paper, the concept of dynamic knowledge base is introduced, which has a mechanism of evolving itself until a proper answer can be found.
Cited by 0
Daniel Goossens · 2010
This paper presents an implemented architecture for easy conception and reorganization of a Boolean knowledge base. As new definitions are added through seamless interaction, the base spontaneously brings up intermingled taxonomies of concepts, which are crucial for knowledge navigation. Complex constraints may be programmatically added by grounding first-order rules. This is illustrated with an example from elementary school geometry.
Cited by 0
Shigeki Sugiyama · 2004
We have much information to be processed in order to get various systems. For getting a desired output, we have now many kinds of AI methods and techniques, which may be able to handle an input information intelligently. However, those methods and techniques are not so flexible enough to get a proper output to an input when an output is not a desired one. That is to say, when the present methods have once produced an output, it will be the final one and it cannot be changed whatever an output's expectation is. In this situation the systems need to have some kind of dynamic knowledge base behavior in treatment, which gives more proper an output to an input. So in this paper, the following themes are discussed: 1) communication method among processes in a system, 2) general mechanism of dynamic behavior of AI and knowledge base, and 3) system structure.
Cited by 0
Haoyang Li, Alexander Zhou, F. Jin et al. · Lecture notes in computer science · 2025
Cited by 0
Ashley George, Adetokunbo Makanju, Evangelos Milios et al. · 2010
Netpal is a web-based dynamic knowledge base system designed to assist network administrators in their troubleshooting tasks, in recalling and storing experience, and in identifying new failure cases and their symptoms. In the context of web hosting environments, Netpal summarises network data and and supports retrieval of relevant organisational experience for system administrators. The system design draws on a variety of domains including knowledge management, information retrieval, machine learning and network management. We describe the system architecture, user interface design, user software testing and future directions for development. 1
Cited by 0
Kostyantyn Kharchenko · Visnyk Universytetu “Ukraina” · 2019
The approach to organizing the automated calculations’ execution process using the web services (in particular, REST-services) is reviewed. The given solution will simplify the procedure of introduction of the new functionality in applied systems built according to the service-oriented architecture and microservice architecture principles. The main idea of the proposed solution is in maximum division of the server-side logic development and the client-side logic, when clients are used to set the abstract computation goals without any dependencies to existing applied services. It is proposed to rely on the centralized scheme to organize the computations (named as orchestration) and to put to the knowledge base the set of rules used to build (in multiple steps) the concrete computational scenario from the abstract goal. It is proposed to include the computing task’s execution subsystem to the software architecture of the applied system. This subsystem is composed of the service which is processing the incoming requests for execution, the service registry and the orchestration service. The clients send requests to the execution subsystem without any references to the real-world services to be called. The service registry searches the knowledge base for the corresponding input request template, then the abstract operation description search for the request template is performed. Each abstract operation may already have its implementation in the form of workflow composed of invocations of the real applied services’ operations. In case of absence of the corresponding workflow in the database, this workflow implementation could be synthesized dynamically according to the input and output data and the functionality description of the abstract operation and registered applied services. The workflows are executed by the orchestrator service. Thus, adding some new functions to the client side can be possible without any changes at the server side. And vice versa, adding new services can impact the execution of the calculations without updating the clients.
Cited by 0Open access
Xinyi Zhu, Jiawei Li, Hao Wang et al. · Zenodo (CERN European Organization for Nuclear Research) · 2023
In recent years, domain-specific knowledge bases (KBs) have been increasingly popular due to their expertise and in-depth representation in a specific domain. Among these domain-specific KBs, financial KBs have attracted considerable attention from academics and industries due to their broad spectrum of downstream applications, such as stock movement prediction, financial fraud detection, and supply chain management. Until now, no datasets including open-domain and domain-specific KBs provide dynamic, up-to-date, and comprehensive financial knowledge, which leads to a fair comparison and broader research among popular financial task models impossible or at least very difficult. We, therefore, construct a dynamic financial KB, HiDy, to address the current limitations discussed above. HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 492,600 relations, 17 entity types, and more than 51,000 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, <em>Macro</em>, <em>Meso</em>,<em> Micro</em>, and<em> Others</em>. Moreover, the robustness of HiDy is a result of the state-of-the-art knowledge extraction and fusion techniques as well as the manual cleaning. For temporality, HiDy's dynamic knowledge is extracted from various resources under different time-granularity to ensure each branch's knowledge is the most up-to-date.
Cited by 0Open access
AGUILERA, Ana Isabel, SOLAIMAN, Basel · OpenGrey (Institut de l'Information Scientifique et Technique) · 2008
Les travaux de recherche que nous présentons dans cette thèse concernent la définition d une méthode d acquisition de connaissance multi-expert dans le cadre du diagnostic médical. En effet, les environnements médicaux et la connaissance associée à ceux-ci ont des caractéristiques spécifiques qui demandent des efforts additionnels dans la conception des systèmes de connaissance. Notre méthode a consisté en trois étapes: 1) la modélisation conceptuelle des agents qui prennent part à la résolution du problème, 2) la mise en œuvre des outils informatiques pour l acquisition de connaissance et 3) la validation de la connaissance acquise. Nous avons accompli les étapes décrites par notre méthode et à la fin, nous avons construit une base de cas basée sur des vrais cas et nous avons compté sur l expérience des experts pour sa validation.
Cited by 0
Zhu, Xinyi, Li, Jiawei, Wang, Hao et al. · Zenodo (CERN European Organization for Nuclear Research) · 2024
HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 506,024 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others. We then give explanations on the various csv files as follows. "hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company". "hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10". For details of HiDy, please refer to our GitHub.
Cited by 0Open access
Xinyi Zhu, Jiawei Li, Hao Wang et al. · Zenodo (CERN European Organization for Nuclear Research) · 2023
HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 501,925 relations, 17 entity types, and more than 51,015 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, <em>Macro</em>, <em>Meso</em>,<em> Micro</em>, and<em> Others</em>. We then give explanations on the various csv files as follows. "hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company". "hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10". For details of HiDy, please refer to our GitHub.
Cited by 0Open access
R. G. Jeroslow, Jinchang Wang · INFORMS Journal on Computing · 1989
We show how the structure of proofs in a Horn clause knowledge base is completely described by certain of the extreme solutions to a suitable “dual” linear constraint set. The extreme points of this linear system are integer vectors, and give the count of the number of times that a given proposition is used in a proof of a “target” proposition. The “primal” to this dual provides the pointwise maximum vector which solves a set of dynamic programming recursions, and the latter recursions are derived from the Horn clause knowledge base. Variation in the facts or in the rules of the knowledge base corresponds to changes in only the criterion vector of the dual linear program. This linear programming approach to inference in expert systems also allows for the detection of “near proofs.” The latter are, by definition, proof structures which would become valid, if only exactly one more fact were known to be true. The first author, Robert G. Jeroslow, deceased August 31, 1988. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
Cited by 27
Xinyi Zhu, Jiawei Li, Hao Wang et al. · Zenodo (CERN European Organization for Nuclear Research) · 2024
HiDy is a hierarchical, dynamic, robust, diverse, and large-scale financial KB that aims to provide various valuable financial knowledge as critical benchmarking data for fair model testing in different financial tasks. Specifically, HiDy currently contains 34 relation types, more than 506,444 relations, 17 entity types, and more than 51,095 entities. The scale of HiDy is steadily growing due to its continuous updates. To make HiDy easily accessible and retrieved, HiDy is organized in a well-formed financial hierarchy with four branches, Macro, Meso, Micro, and Others. We then give explanations on the various csv files as follows. "hidy.nodes.entity_type.csv" includes a mapping dictionary of entities with a specific entity type. The meta data is ID, name, (code), Label. For example, "hidy.nodes.company.csv" includes "0,东诚药业,002675.SZ,company", "1,大庆华科,000985.SZ,company". "hidy.relationships.relation_type.csv" includes quadruple knowledge with a specific relation type. The meta data is START_ID, END_ID, TYPE, time. For example, "hidy.relationships.cooperate.csv" includes "2197,245,cooperate,2019/9/17 12:00, "1165,756,cooperate,2020/8/2 17:10". For details of HiDy, please refer to our GitHub.
Cited by 0Open access
Hsan Sandar Win, Andrew J. Walters, Cheng-Chew Lim et al. · ArXiv.org · 2026
In this paper, the concept of Dynamic Contextual Mission Data (DCMD) is introduced to develop an ontology-driven dynamic knowledge base for Uninhabited Ground Vehicles (UGVs) at the tactical edge. The dynamic knowledge base with DCMD is added to the UGVs to: support enhanced situation awareness; improve autonomous decision making; and facilitate agility within complex and dynamic environments. As UGVs are heavily reliant on the a priori information added pre-mission, unexpected occurrences during a mission can cause identification ambiguities and require increased levels of user input. Updating this a priori information with contextual information can help UGVs realise their full potential. To address this, the dynamic knowledge base was designed using an ontology-driven representation, supported by near real-time information acquisition and analysis, to provide in-mission on-platform DCMD updates. This was implemented on a team of four UGVs that executed a laboratory based surveillance mission. The results showed that the ontology-driven dynamic representation of the UGV operational environment was machine actionable, producing contextual information to support a successful and timely mission, and contributed directly to the situation awareness.
Cited by 0Open access
Kaden Marchetti, Andrija Sevaljevic, Alex Diviney et al. · 2024
Whereas interactive dynamic visualization tools have been successfully developed and used for teaching some topics in computational theory (CT), there remains a noticeable lack of such tools for teaching NP-completeness which continues to be widely taught using paper-and-pencil methods. Despite its important theoretical and practical value, NP-completeness-and mapping reductions in NP-completeness in particular-tends to be a challenging concept for CT students to understand. We present an open-source web app called Redux that provides a dynamic interactive user interface atop a practical knowledge base of NP-complete problems, reductions, and solution algorithms. A key feature of the interface is the visualization of arbitrary problem instances, mapping reductions, solutions, and gadgets-including those reachable via transitivity. The web app is designed to make the knowledge base extensible, allowing students to contribute and compare their reductions and solutions to those already available. Two surveys were administered, with respondents overwhelmingly indicating that Redux helped them to better understand mapping reductions; that they would prefer using Redux to solve similar problems manually; and that Redux makes learning NP-complete reductions more enjoyable. Redux is accessible online via https://redux.portneuf.cose.isu.edu/.
Cited by 3
Long Zhao, Xu Yin, Yanyan Wang et al. · Lecture notes in computer science · 2024
Cited by 2
Hsan Sandar Win, Andrew J. Walters, Cheng-Chew Lim et al. · arXiv (Cornell University) · 2026
In this paper, the concept of Dynamic Contextual Mission Data (DCMD) is introduced to develop an ontology-driven dynamic knowledge base for Uninhabited Ground Vehicles (UGVs) at the tactical edge. The dynamic knowledge base with DCMD is added to the UGVs to: support enhanced situation awareness; improve autonomous decision making; and facilitate agility within complex and dynamic environments. As UGVs are heavily reliant on the a priori information added pre-mission, unexpected occurrences during a mission can cause identification ambiguities and require increased levels of user input. Updating this a priori information with contextual information can help UGVs realise their full potential. To address this, the dynamic knowledge base was designed using an ontology-driven representation, supported by near real-time information acquisition and analysis, to provide in-mission on-platform DCMD updates. This was implemented on a team of four UGVs that executed a laboratory based surveillance mission. The results showed that the ontology-driven dynamic representation of the UGV operational environment was machine actionable, producing contextual information to support a successful and timely mission, and contributed directly to the situation awareness.
Cited by 0Open access
Rafaela E. Marco, Miguel M. Colina · NATO ASI series. Series F : Computer and system sciences · 1992
Cited by 2
Xinyi Zhu, Hao Xin, Yanyan Shen et al. · Lecture notes in computer science · 2023
Cited by 3
Jingjing Jiang, JiaShun Wang, Dandan Wang et al. · Advances in intelligent systems and computing · 2020
Cited by 0
Cornelia M. Verspoor, Robert Dale, Stephen J. Green et al. · 1998
Users of the World Wide Web have needs and interests which can help to determine what of the vast quantities of information available might be relevant to them. Intelligent agents might be used to select content for a particular user. However, it is also important to consider how that content is provided to a user. We suggest that this information presentation must also take into consideration the needs of a user, and discuss a set of agents which utilizes natural language generation techniques to present information in an appropriate way. In this paper we describe two systems we have built which dynamically generate descriptions of knowledge base entities, and consider the extension of the techniques used there for multilingual information presentation. We describe the notion of a phrasal lexicon as a basis for dynamic object description, and propose a model for dynamic multilingual description which builds on that notion.
Cited by 0