Conceptual Graphs Research Articles

Stock Trend Prediction with Machine Learning: Incorporating Inter-Stock Correlation Information through Laplacian Matrix

Predicting stock trends in financial markets is of significant importance to investors and portfolio managers. In addition to a stock’s historical price information, the correlation between that stock and others can also provide valuable information for forecasting future returns. Existing methods often fall short of straightforward and effective capture of the intricate interdependencies between stocks. In this research, we introduce the concept of a Laplacian correlation graph (LOG), designed to explicitly model the correlations in stock price changes as the edges of a graph. After constructing the LOG, we will build a machine learning model, such as a graph attention network (GAT), and incorporate the LOG into the loss term. This innovative loss term is designed to empower the neural network to learn and leverage price correlations among different stocks in a straightforward but effective manner. The advantage of a Laplacian matrix is that matrix operation form is more suitable for current machine learning frameworks, thus achieving high computational efficiency and simpler model representation. Experimental results demonstrate improvements across multiple evaluation metrics using our LOG. Incorporating our LOG into five base machine learning models consistently enhances their predictive performance. Furthermore, backtesting results reveal superior returns and information ratios, underscoring the practical implications of our approach for real-world investment decisions. Our study addresses the limitations of existing methods that miss the correlation between stocks or fail to model correlation in a simple and effective way, and the proposed LOG emerges as a promising tool for stock returns prediction, offering enhanced predictive accuracy and improved investment outcomes.

Searching COVID-19 Clinical Research Using Graph Queries: Algorithm Development and Validation.

Since the beginning of the COVID-19 pandemic, >1 million studies have been collected within the COVID-19 Open Research Dataset, a corpus of manuscripts created to accelerate research against the disease. Their related abstracts hold a wealth of information that remains largely unexplored and difficult to search due to its unstructured nature. Keyword-based search is the standard approach, which allows users to retrieve the documents of a corpus that contain (all or some of) the words in a target list. This type of search, however, does not provide visual support to the task and is not suited to expressing complex queries or compensating for missing specifications. This study aims to consider small graphs of concepts and exploit them for expressing graph searches over existing COVID-19-related literature, leveraging the increasing use of graphs to represent and query scientific knowledge and providing a user-friendly search and exploration experience. We considered the COVID-19 Open Research Dataset corpus and summarized its content by annotating the publications' abstracts using terms selected from the Unified Medical Language System and the Ontology of Coronavirus Infectious Disease. Then, we built a co-occurrence network that includes all relevant concepts mentioned in the corpus, establishing connections when their mutual information is relevant. A sophisticated graph query engine was built to allow the identification of the best matches of graph queries on the network. It also supports partial matches and suggests potential query completions using shortest paths. We built a large co-occurrence network, consisting of 128,249 entities and 47,198,965 relationships; the GRAPH-SEARCH interface allows users to explore the network by formulating or adapting graph queries; it produces a bibliography of publications, which are globally ranked; and each publication is further associated with the specific parts of the query that it explains, thereby allowing the user to understand each aspect of the matching. Our approach supports the process of query formulation and evidence search upon a large text corpus; it can be reapplied to any scientific domain where documents corpora and curated ontologies are made available.

A framework for trust-related knowledge transfer in human–robot interaction

Trustworthy human–robot interaction (HRI) during activities of daily living (ADL) presents an interesting and challenging domain for assistive robots, particularly since methods for estimating the trust level of a human participant towards the assistive robot are still in their infancy. Trust is a multifaced concept which is affected by the interactions between the robot and the human, and depends, among other factors, on the history of the robot’s functionality, the task and the environmental state. In this paper, we are concerned with the challenge of trust transfer, i.e. whether experiences from interactions on a previous collaborative task can be taken into consideration in the trust level inference for a new collaborative task. This has the potential of avoiding re-computing trust levels from scratch for every new situation. The key challenge here is to automatically evaluate the similarity between the original and the novel situation, then adapt the robot’s behaviour to the novel situation using previous experience with various objects and tasks. To achieve this, we measure the semantic similarity between concepts in knowledge graphs (KGs) and adapt the robot’s actions towards a specific user based on personalised interaction histories. These actions are grounded and then verified before execution using a geometric motion planner to generate feasible trajectories in novel situations. This framework has been experimentally tested in human–robot handover tasks in different kitchen scene contexts. We conclude that trust-related knowledge positively influences and improves collaboration in both performance and time aspects.

Characterizations of Minimal Dominating Sets in γ-Endowed and Symmetric γ-Endowed Graphs with Applications to Structure-Property Modeling

Claude Berge (1987) introduced the concept of k-extendable graphs, wherein any independent set of size k is inherently a constituent of a maximum independent set within a graph H=(V,E). Graphs possessing the property of being 1-extendable are termedas Berge graphs. This introduction gave rise to the notion of well-covered graphs and well-dominated graphs. A graph is categorized as well-covered if each of its maximal independent sets is, in fact, a maximum independent set. Similarly, a graph attains the classification of well-dominated if every minimal dominating set (DS) within it is a minimum dominating set. In alignment with the concept of k-extendable graphs, the framework of (k,γ)-endowed graphs and symmetric (k,γ)-endowed graphs are established. In these graphs, each DS of size k encompasses a minimum DS of the graph. In this article, a study of γ-endowed dominating sets is initiated. Various results providing a deep insight into γ-endowed dominating sets in graphs such as those characterizing the ones possessing a unique minimum DS are proven. We also introduce and study the symmetric γ-endowed graphs and minimality of dominating sets in them. In addition, we give a solution to an open problem in the literature. which seeks to find a domination-based parameter that has a correlation coefficient of ρ>0.9967 with the total π-electronic energy of lower benzenoid hydrocarbons. We show that the upper dominating number Γ(H) studied in this paper delivers a strong prediction potential.

Knowledge Graphs underpinning ship digital twins for decarbonisation options assessment

We propose the concept of a Knowledge Graph as a data management and inference machinery that underpins digital twins of ships. The Knowledge Graph is a directed graph connecting dependent and independent model variables of interest in the digital twin, where the correlations between variables are continuously updated based on data received from the physical ship. The paper outlines a methodology for constructing the Knowledge Graph and proposes metrics that help to calculate the effectiveness of decarbonization solutions based on changes to the strength of data correlations. The proposed methodology allows for the extrapolation of decarbonization technology potential across specific vessels, fleets, operational patterns, and lifecycle phases.

Spatialities between property and the commons: an interval of tolerance

This paper examines the relations of ‘space’ with ‘property’ and ‘commons’. Property is an exclusionary mechanism that regulates human relationships through space based on ownership, boundary, and control. Contrarily, the commons is a spatial practice of encounter, collaboration, and sharing, open to all kinds of participation of the multitude. With a research methodology grounded in the principle of ‘tolerance’, this study questions the spatialities between property and the commons, with or without coexistence and communication. To achieve this, a diagrammatical method for ‘a theoretical reading over an interval’ is generated, which enables a debate on the property and the commons over a conceptual graph of connections of ‘spatial tendencies’, ‘theoretical structures’, and ‘spatial activism’. The ‘interval of tolerance’ graph reveals the connections as a tolerance environment for encountering differences and ensuring spatial relations. Thus, the expansion of networks of connections means the expansion of tolerance. The study concludes that the interval of tolerance narrows towards property but broadens towards the commons, which means spatial toleration is high in the commons, but low in property.

Towards resources optimization in deploying service function chains with shared protection

Emerging artificial intelligence techniques enable the Internet-connected devices automatically generate massive SFC requests in scenarios with ultra-reliability demands such as unmanned vehicle systems, smart factories. In such scenarios, it is imperative to deploy these huge amounts of SFCs in a fault-tolerant manner. The existing works on fault-tolerant SFC deployment employs the dedicated SFC backup protection with the resources redundancy of at least 100%, which addresses the ratio between the backup and primary resource consumptions. Due to this, the dedicated SFC protection likely prevents these reliable SFCs from being massively deployed. To tackle this challenge, for the first time, this work studies how to enhance the resource utilization by deploying SFCs with shared protection. First, we introduce new concepts of SFC protection set and sharing-risk SFC graph (SCG). Next, we define a new problem called SFCs embedding with SCG-based shared protection. Then, we propose a heuristic algorithm called SCG-based SFC embedding and protecting (SCG-SEP), which is proved to be logarithm-approximate. Extensive simulations show that SCG-SEP outperforms the benchmarks by an average of 12.25% and 43.67%.

Topological awareness towards collision-free multi-axis curved layer additive manufacturing

We present a topology-aware computational framework that enables global collision-free and support-structure-free material extrusion for curved layer multi-axis printing of a range of high-genus and simply connected models. The nature of multi-axis additive manufacturing facilitates continuous variation of build direction, which paves the way for numerous approaches of geometry-based curved layer design. However, due to unawareness of global topological features, prevention of collision between the printer nozzle and the workpiece can either remain uncertain or demand for exhaustive algorithmic approaches, depending on the topological and geometrical complexity of a given mesh model. In this paper, we present a topological analysis framework that draws inspiration from the concepts of Reeb graph and Morse theory, to distinguish between collision-prone and collision-free regions of mesh models. We provide an exact definition for global collision-inducing features in regions of risk and optimise the nozzle orientation vector field to avoid global collisions whilst adhering to the overhang angle constraints. A new shape analysis method is then proposed to find the model orientation which maximises the manufacturability of bifurcating simply connected models. To validate our algorithmic framework, several high-genus and bifurcating simply connected models are printed using a robotic multi-axis printer. The experimental results demonstrate the feasibility and effectiveness of our framework for minimising global collisions in multi-axis curved layer additive manufacturing for a range of mesh models.

Topological numbers of fuzzy soft graphs and their applications in globalizing the world by mutual trade

In this research draft, by keeping in view, the importance of Zagreb numbers, first we defined some familiar graph families and their degrees in fuzzy soft environment, and then by converting these two novel topological numbers in fuzzy soft framework, their formulae are calculated for these graphical networks. An application of international trade using two kinds of routes is also discussed in the article, and by comparing the results efficiency of both the numbers is compared and analyzed how topological descriptors are useful in examining the progress and profit in the countries, that are a part of the project. Graphs are used in the modeling of links and processes within physical, biological, social, and information systems. A fuzzy graph is the most adaptable tool in mathematics, which describes the fuzzy relationship between objects. Fuzzy graphs are very helpful to give more accuracy to the system as compared to crisp graphs. A classification of the universe with respect to certain specified parameters is known as a soft set. It is a new method for simulating ambiguity and uncertainty. Soft set theory was created by Molodtsov in 1999 as a method for simulating vagueness and uncertainty. Soft set theory is presently used widely in academia to address decision-making issues. The concept of soft graphs is used to provide a parameterized point of view for graphs. In many areas of mathematics and chemistry, as well as in network theory, spectral graph theory, and molecular chemistry, the Zagreb numbers are crucial graph parameters. Due to the importance and significance of Zagreb numbers, in this research article we define these graph parameters in fuzzy soft environment and then derived the fundamental formula for first and second Zagreb numbers of some popular graph families. Also by keeping in view the importance of graph theory in solving decision making problems in business industry, and the most generic behavior of fuzzy soft graph due to its parameterized nature we use our work in application of decision making in trade among different nations.

DOMINATION IN (2,1)-FUZZY GRAPHS AND ITS APPLICATION

The notion of a fuzzy graph (FG) and its expanded variations have been devised to address several real-world issues including imprecision, such as decision-making, networking, shortest path, and so forth. The generalization of FG theory to circumstances where imprecision is characterized by differences in the values of membership and non-membership grades is the basis of this study. The purpose of this study is to present the (2,1)-fuzzy set graph concept. Furthermore, in a (2,1)-fuzzy environment, this study examines the idea of domination theory. More specifically, the theory related to (2,1)-fuzzy graphs is presented along with illustrative examples, introducing the framework. Additionally, the domination theory associated with (2,1)-fuzzy graphs is developed. Finally, a numeral example is presented to explain the computing of domination in (2,1)-fuzzy graph in the specific application.

M-step inverse fuzzy mixed competition graphs

The notion of competition graphs has a wide range of applications and has been utilized in designing various ecological problems and real-world competitions. Here, the idea of m-step inverse fuzzy mixed competition graphs has been introduced and some of its basic properties have been discussed. Also, some ideas associated with the concept of m-step inverse fuzzy mixed competition graphs, such as m-step inverse fuzzy neighborhood graph, inverse fuzzy mixed economic competition graph, and m-step inverse fuzzy mixed economic competition graph have been defined. Our motive was to focus on the real-life problems that can be properly addressed with graphs involving directed and undirected edges. In this case, the concept of an m-step fuzzy competition graph is not appropriate for solving these problems. However, the idea of m-step inverse fuzzy mixed competition graphs is more relevant to address them. An application of m-step inverse fuzzy mixed competition graphs has been identified as a suitable solution to a real-life problem.

Modelling transmission dynamics and genomic diversity in a recombining parasite population

The genomic diversity of a parasite population is shaped by its transmission dynamics but superinfection, cotranmission and recombination make this relationship complex and hard to analyse. This paper aims to simplify the problem by introducing the concept of a genomic transmission graph with three basic parameters: the effective number of hosts, the quantum of transmission and the crossing rate of transmission chains. This enables rapid simulation of coalescence times in a recombining parasite population with superinfection and cotransmission, and it also provides a mathematical framework for analysis of within-host variation. Taking malaria as an example, we use this theoretical model to examine how transmission dynamics and migration affect parasite genomic diversity, including the effective recombination rate and haplotypic metrics of recent common ancestry. We show how key transmission parameters can be inferred from deep sequencing data and as a proof of concept we estimate the Plasmodium falciparum transmission bottleneck. Finally we discuss the potential applications of this novel inferential framework in genomic surveillance for malaria control and elimination. Online tools for exploring the genomic transmission graph are available at d-kwiat.github.io/gtg.

Fuzzy graphs and their applications in finding the best route, dominant node and influence index in a network under the hesitant bipolar-valued fuzzy environment

This paper introduces the concept of hesitant bipolar-valued fuzzy graph (HBVFG), which captures the two opposing perspectives, namely the positive and negative opinions. The novelty, importance and implications of this concept are illustrated by some results, examples, and graphical representations. There are, respectively, some theoretical terms of graphs such as partial directed hesitant bipolar-valued fuzzy subgraph (HBVFSG), directed HBVFSG, directed spanning HBVFSG, strong directed HBVFG and complete directed HBVFG which are introduced. The operations, such as Cartesian, direct, lexicographical, and strong products, are also defined between two HBVFGs with examples. The mapping relations, such as homomorphism, isomorphism, weak isomorphism, and co-weak isomorphism, are derived with an example. The applications of directed HBVFGs with algorithms for finding the optimal path in a network and the dominant node and influence of index with the self-persistence degree of a node in a social network are presented. For each problem, an algorithm is developed and its effectiveness is demonstrated by examples. The proposed concept is assessed in terms of theory and practice. The benefits of the proposed solution are highlighted and a clear comparison is made with the existing methods.

On Some Bounds of Degree Based Topological Indices for Total Graphs

In this paper, we discuss the concept of total graph and computed some topological indices. If $\Theta$ is a simple graph, then the elements of $\Theta$ are the vertices $\Theta_V$ and edges $\Theta_E$. For $ e=u\acute{u}\in \Theta_E$, the vertex $u$ and edge $e$, as well as $\acute{u}$ and $e$, are incident. We define the general harmonic $(GH)$ index and general sum connectivity $(GS)$ index for graph $\Theta$ regarding incident vertex-edge degrees as: $H_s^{\alpha}(\Theta)=\sum_{e\acute{u}}\big(\frac{2}{\aleph_{\acute{u}}+\aleph_{e}}\big)^{\alpha}$ and $\hat{\chi}_s^{\alpha}(\Theta)=\sum_{e\acute{u}}(\aleph_{\acute{u}}+\aleph_{e})^{\alpha}$, where $\alpha$ is any real number. In this article, we derive the closed formulas for a few standard graphs for $(GH)$ and $(GS)$ indices and then go on to calculate the lowest and the greatest general harmonic index, as well as the general sum-connectivity index, for various graphs that correspond to their total graphs.

Обзор и анализ представлений графов знаний

With the development of artificial intelligence, knowledge graphs are becoming increasingly important in information systems. The article reviews the definitions and representations of knowledge graphs by different authors. The purpose of the study is to form an idea of knowledge graphs for subsequent research. To determine the essence of the concept of the knowledge graph, its history and evolution are considered, as well as a review and comparative analysis of existing definitions over the past 10 years using induction and deduction methods. The main accents on which the researchers relied in their works are also highlighted. As a result, the author's idea of knowledge graphs is derived by the analysis and synthesis methods

Paths, Proofs, and Perfection: Developing a Human-Interpretable Proof System for Constrained Shortest Paths

People want to rely on optimization algorithms for complex decisions but verifying the optimality of the solutions can then become a valid concern, particularly for critical decisions taken by non-experts in optimization. One example is the shortest-path problem on a network, occurring in many contexts from transportation to logistics to telecommunications. While the standard shortest-path problem is both solvable in polynomial time and certifiable by duality, introducing side constraints makes solving and certifying the solutions much harder. We propose a proof system for constrained shortest-path problems, which gives a set of logical rules to derive new facts about feasible solutions. The key trait of the proposed proof system is that it specifically includes high-level graph concepts within its reasoning steps (such as connectivity or path structure), in contrast to, e.g., using linear combinations of model constraints. Thus, using our proof system, we can provide a step-by-step, human-auditable explanation showing that the path given by an external solver cannot be improved. Additionally, to maximize the advantages of this setup, we propose a proof search procedure that specifically aims to find small proofs of this form using a procedure similar to A* search. We evaluate our proof system on constrained shortest path instances generated from real-world road networks and experimentally show that we may indeed derive more interpretable proofs compared to an integer programming approach, in some cases leading to much smaller proofs.

Topological numbers of fuzzy soft graphs and their application

The diagram kind of a graph is used to show accumulated data. Graphs can be utilized for a variety of purposes because this data can be either quantitative or qualitative. Graphs can be used to model different relationships and processes in physical, biological, and social media marketing systems, and in finding directions on a map. A graph with properties attached to its nodes and edges that emphasize its applicability to real-world systems is sometimes called a network. The idea of fuzzy sets has developed in numerous ways and across many areas since its establishment in 1965. Applications of this theory can be found in numerous fields for instance in recognition of patterns, management science, AI, computer science, medicine, also in control engineering. The progress of mathematics has reached a very high level and continues now. While classical graph theory is widely applied in several domains, there are instances where its outcomes can be subject to uncertainty. In order to address this challenge, the utilization of the fuzzy theory of graphs is adopted, as it offers more accurate outcomes. There is a lack of a parameterization tool in fuzzy graph theory, as a consequence Molodtsov introduced soft set theory, which is a rather recent way to talk about ambiguity and vagueness. It is becoming more and more popular among scholars and is a novel approach to uncertainty and ambiguity simulation. The concept of soft graphs offers a parameterized perspective on graphs. In this article, we defined some familiar graph families in a fuzzy soft (FS) environment and by calculating their degrees, derived important results for two versions of Sombor numbers. In the end, we discussed an application of calculated results and by comparison, checked the efficiency of Sombor numbers in a FS framework.

A Study on Exact Deg-Centric Graphs of Graphs

The exact deg-centric graph of a simple, connected graph [Formula: see text], denoted by [Formula: see text], is a graph constructed from [Formula: see text] such that [Formula: see text] and [Formula: see text]. In this paper, the concepts of exact deg-centric graphs and iterated exact deg-centrication of a graph are introduced and discussed.

Research on conceptual graph gallery-based cognitive communication method for geographical conceptual modeling

Geographic modeling is considered as an effective way to solve geographic problems. Geographic conceptual modeling is the first step of geographic modeling, in which modelers can fully exchange modeling ideas, thereby achieving a common understanding of geographic system and guiding subsequent geographic modeling process. However, due to the diverse research backgrounds of modelers, it is challenging for them to exchange modeling ideas with one another. This paper provides a visual cognitive communication method for modelers by constructing a conceptual graph gallery, and then improves the efficiency of geographic conceptual modeling. A multidimensional description method that describes modeling cognition from multiple perspectives, the conceptual graph gallery that includes concept items and conceptual graphs, and the conceptual graph gallery-based cognitive communication methods are designed in this paper. Finally, a case study involving the construction of a hydrological conceptual graph gallery is designed to illustrate the feasibility of conceptual graph gallery-based cognitive communication.

Product of Semi – Lattices of Certain Graphs

Introduction: In this article, author tries to construct a relation between graphs of product of meet-semilattices L = L_1 X L_2, where L_1 and L_2 are two semilattices and obtain some properties of such graphs. Author investigated that for meet-semilattices L_1 and L_2 has a cycle of length n-1 and n.
 Objectives: author reveals that if L_1 and L_2 be two meet-semilattices with 0 and L = L_1 X L_2, then it is a star graph. In this paper, we have covered some definitions, examples and theorems on zero devisor graph edge of a 4 - cycles or a 5 - cycles. Γ(L) is a star graph.
 Methods: Theorem 1.1 [9] The zero-divisor graph of a finite meet-semilattice with only one atom is the empty graph. The zero-divisor graph of the meet semilattice is the empty graph. However, this does not hold for infinite meet-semilattices with one atom. For consider, the infinite meet-semilattice, where the descending dots represent infinite descending chain. It has only one atom c but its graph Γ(L) is an infinite star graph.
 Theorem 1.2 [12] Every disconnected graph cannot be a graph of any meet- semilattice L with 0.
 Remark 1.2 A graphs of product of meet-semilattices and obtain some properties of such graphs. In this section, we consider two integral meet-semilattices L_1 and L_2 with L ∼=L_1 X L_2 and show that if ∣L_1∣ = m+1, ∣L_2∣ = n+1, then Γ(L) is the complete bipartite graph K (m, n).
 Results: If L does not contain any atom, then any edge in Γ(L) is contained in a cycle of length ≤ 6, and therefore Γ(L) is a union of 4 - cycles and 5 - cycles. Let L be a meet-semilattice with 0. If Γ(L) contains a cycle, then the core K of Γ(L) is a union of 4- cycles and 5 – cycles and any vertex in Γ(L) is either a vertex of the core K of Γ(L) or is a pendant of Γ(L). Let L_1 and L_2 be two meet-semilattices with 0 and L = L_1 X L_2. Then exactly one of the following holds:
 
 Γ(L) has a cycle of length n-1 or n (that is gr Γ(L)≤ n).
 Γ(L) is a star graph.
 
 Conclusions: In this article we have studied the concept of the zero-divisor graph derived from meet-semilattice L with 0 on the lines of Anderson and Livingston [6]. Also, we generalized certain results from Demeyer, Mckenzie and Schneider [18] to meet-semilattice L with 0.