Relevant bibliographies by topics / Knowledge representation (Information theory)

Academic literature on the topic 'Knowledge representation (Information theory)'

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Published: 4 June 2021
Last updated: 31 July 2024

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Journal articles on the topic "Knowledge representation (Information theory)"

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Haddawy, Peter, and Larry Rendell. "Planning and decision theory." Knowledge Engineering Review 5, no. 1 (March 1990): 15–33. http://dx.doi.org/10.1017/s026988890000521x.

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Research on planning in AI can be separated into the two major areas: plan generation and plan representation. Most AI planners to date have been based on the STRIPS planning representation. This representation has a number of limitations. Much recent work in plan representation has addressed these limitations. It was shown that Decision Theory can be used to remove a number of the limitations. Furthermore, the decision theoretic framework provides a precise definition of rational behaviour. There remain open questions within decision theory regarding belief revision and causality. It should be noted that these problems are not artifacts of the representation. Rather they arise because the rich representation allows their formulation. Some work integrating AI and decision theoretic approaches to planning has been done but this remains a largely untouched research area.We see two main avenues for fruitful research. First, the straightforward decision theoretic formulation of planning is computationally impractical. Techniques need to be developed to do efficient decision theoretic planning. Work in AI plan generation has exploited information contained the structure of qualitative representations to guide efficient plan construction. These techniques should be applied to decision theoretic representations as well. Second, AI has developed many representations that allow useful structuring of knowledge about the world. Decision Theory has concentrated on representing beliefs and desires. Integration of AI and decision theoretic representations would yield powerful representation languages. Some of the benefits of such work can already be seen in the research combining temporal and decision theoretic representations.
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Popping, Roel, and Inge Strijker. "Representation and integration of sociological knowledge using knowledge graphs." Social Science Information 36, no. 4 (December 1997): 731–47. http://dx.doi.org/10.1177/053901897036004006.

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The representation and integration of sociological knowledge using knowledge graphs, a specific kind of semantic network, is discussed. Knowledge is systematically searched; this reveals inconsistencies, reducing superfluous research and knowledge, and showing gaps in a theory. This representation is conceivable under certain conditions, which are discussed. A graph for sociological theories about labour markets is presented.
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Joubert, M., M. Fieschi, and F. Volot. "Review of Biomedical Knowledge and Data Representation with Conceptual Graphs." Methods of Information in Medicine 37, no. 01 (1998): 86–96. http://dx.doi.org/10.1055/s-0038-1634504.

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Abstract:The basis of conceptual graphs theory is an ontology of types of concepts. Concepts issued from the ontology are interlinked by semantic relationships and constitute canonical conceptual graphs. Canonical graphs may be combined to derive new conceptual graphs by means of formation rules. This formalism allows to separate knowledge representation into a conceptual level and a domain-dependent level, and enables to share and reuse a representation. This paper presents conceptual graph applications to biomedical data and concept representation, classification systems, information retrieval, and natural language understanding and processing. A discussion on the unifying role conceptual graphs theory plays in the implementation of knowledge-based systems is also presented.
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Zhitomirsky-Geffet, Maayan. "Towards a diversified knowledge organization system." Journal of Documentation 75, no. 5 (September 9, 2019): 1124–38. http://dx.doi.org/10.1108/jd-10-2018-0163.

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Purpose The need for inclusive and logically consistent representation of diverse and even confronting viewpoints on the domain knowledge has been widely discussed in the literature in the past decade. The purpose of this paper is to propose a generic model for building an open coherent diversified knowledge organization system (KOS). Design/methodology/approach The proposed model incorporates a generic epistemological component, the validity scope type, assigned to each statement in the constructed KOS. Statements are clustered by their association with various validity scope types into internally coherent subsystems. These subsystems form a knowledge organization network connected through the universal (consensual) subsystems with more than one validity scope type. The model extends the Galili’s Cultural Content Representation paradigm, which divides the knowledge content of a scientific theory into two confronting parts: body and periphery. Findings The knowledge organization network model makes it possible to comparatively examine similarities and differences among various viewpoints and theories on the domain knowledge. The presented approach conforms with the principle of Open Knowledge Network initiative for creation of open accessible knowledge. Practical implications The proposed model can be used for ontological reasoning by a variety of information services, such as ontology-based decision-support and learning systems, diversified search and customer management applications. Social implications The model enables explicit representation of social and cultural minority voices and historical knowledge in the KOS. Originality/value The main contribution of the proposed model is that it generalizes and enhances various previously proposed representations of epistemological aspects of KOS and allows for multiple inter-linked subsystems to coherently co-exist as part of the extensible network.
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Rousi, Antti Mikael, Reijo Savolainen, and Pertti Vakkari. "A typology of music information for studies on information seeking." Journal of Documentation 72, no. 2 (March 14, 2016): 265–76. http://dx.doi.org/10.1108/jd-01-2015-0018.

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Purpose – A need to renew music-related information notions arises from both information-seeking models and literature of musical semiotics. The purpose of this paper is to create a music information typology, which aims at facilitating the examination of music information types at varying levels of abstraction in the context of information seeking. Design/methodology/approach – Literature of musical semiotics and information seeking are juxtaposed to develop a novel approach to music-related information. The grounding concepts are Bruner’s enactive, iconic and symbolic modes of representation. The modes of representation offer a universal scheme of knowledge that is applied to the domain of music by defining their content through Tarasti’s Theory of Musical Semiotics. Findings – This conceptual paper results in a music information typology ranging from the enactive music information representations to the abstract ones as follows. Music making as the first mode of enactive representations; music listening as the second mode of enactive representations; iconic representations of music; technological models of music as the first mode of symbolic representations; and ideological models of music as the second mode of symbolic representations. Originality/value – The present paper develops a music information typology that encompasses broadly different music information facets by categorizing music information sources according to their level of abstraction. When applied into empirical research, the typology opens a new window into the perceived roles of music information types in the context of information seeking.
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de Mello, Flávio Luis, and Roberto Lins de Carvalho. "Knowledge Geometry." Journal of Information & Knowledge Management 14, no. 04 (December 2015): 1550028. http://dx.doi.org/10.1142/s0219649215500288.

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This paper aims to present what we call knowledge geometry, an alternative theory for spatial representation of features related to information processing, information management, and knowledge management. It is a unique geometric approach for representing intuition, reification, interpretation, and deduction processes, as well as their relations. We employ the concept of cultural filter and use what we call real, conceptual, and symbolic planes in order to support transformations which occur along the perception of a phenomenon. After that, we discuss the use of evaluation systems to judge concepts and also the use of semantic systems as a communication language. Finally, a framework of the knowledge acquisition process in the field of the proposed theory is offered, proving the feasibility of its automation.
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Radhika, B. "Ground-breaking Theory of Knowledge Representation Practices for Information Sharing in IT Organization." September 2022 4, no. 3 (July 29, 2022): 125–43. http://dx.doi.org/10.36548/jitdw.2022.3.001.

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Sharing information has become very important in the proper use of information assets, and the reason for this is that sharing information can be considered the most important part of an organization because information from organizations must be transferred and participated in order to be known and understood, wherein a clear and unambiguous information is considered a key criterion. To stimulate creativity, information sharing or integration is used to bring disparate pieces of knowledge together. Many current information sharing practices, such as training and development programs, IT systems, reports, official documents, and hard-working groups, are examples of integrating information. By integrating information everywhere to improve the quality of products and services, increases responsiveness to customer needs, develop new capabilities, and improve every aspect of the environment. This study reviews the ground-breaking theory behind information sharing in an organization. From the author’s perspective, this is the first study which gives a complete overview about knowledge representation.
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Astaneh, Mahboobeh Farashbashi. "Representationalism in Knowledge Organization and Information Retrieval: Cheer or Criticism?" KNOWLEDGE ORGANIZATION 50, no. 7 (2023): 475–88. http://dx.doi.org/10.5771/0943-7444-2023-7-475.

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The purpose of this paper is to critically analyze the representational approach to language using the concept of ‘Representationalism’ in philosophy and a new framework referred to in this paper as Information Retrieval Action (IRA). IRA is a theoretical construct based on Information Retrieval (IR) theory. Therefore, the methodology employed in this study is philosophical and speculative. It examines and discusses representationalism in both the mental (cognitive) and linguistic dimensions, incorporating concepts from the philosophy of mind and the philosophy of language as methodological approaches. ‘Concept’ and ‘Meaning’ emerge as two critical semantic elements when considering language as a semiotic phenomenon. Representationalism in IRA is rooted in logical positivism, which serves as the foundation for interpreting meaning and concept based on mental representation. In response, the paper proposes an alternative non-representational approach to the semantic elements of language (meaning and concept) based on the philosophy of pragmatism within the IRA framework. While the emergence of new technologies like ontologies implicitly criticizes representationalism in IRA, previous research has not explicitly addressed the theoretical and philosophical criticism of representationalism within the IRA framework.
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IVÁNEK, JIŘÍ. "REPRESENTATION OF EXPERT KNOWLEDGE AS A FUZZY AXIOMATIC THEORY." International Journal of General Systems 20, no. 1 (December 1991): 55–58. http://dx.doi.org/10.1080/03081079108945013.

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Chen, Yen-Liang, and Fang-Chi Chi. "Summarization of information systems based on rough set theory." Journal of Intelligent & Fuzzy Systems 40, no. 1 (January 4, 2021): 1001–15. http://dx.doi.org/10.3233/jifs-201160.

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In the rough set theory proposed by Pawlak, the concept of reduct is very important. The reduct is the minimum attribute set that preserves the partition of the universe. A great deal of research in the past has attempted to reduce the representation of the original table. The advantage of using a reduced representation table is that it can summarize the original table so that it retains the original knowledge without distortion. However, using reduct to summarize tables may encounter the problem of the table still being too large, so users will be overwhelmed by too much information. To solve this problem, this article considers how to further reduce the size of the table without causing too much distortion to the original knowledge. Therefore, we set an upper limit for information distortion, which represents the maximum degree of information distortion we allow. Under this upper limit of distortion, we seek to find the summary table with the highest compression. This paper proposes two algorithms. The first is to find all summary tables that satisfy the maximum distortion constraint, while the second is to further select the summary table with the greatest degree of compression from these tables.
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Dissertations / Theses on the topic "Knowledge representation (Information theory)"

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Smith, Julian P. "Neural networks, information theory and knowledge representation." Thesis, University of Edinburgh, 1996. http://hdl.handle.net/1842/20801.

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Plate, Tony A. "Holographic reduced representation : distributed representation for cognitive structures /." Stanford, Calif. : CSLI, 2003. http://www.loc.gov/catdir/toc/uchi051/2003043513.html.

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Khor, Sebastian W. "A fuzzy knowledge map framework for knowledge representation /." Access via Murdoch University Digital Theses Project, 2006. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20070822.32701.

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Ding, Yingjia. "Knowledge retention with genetic algorithms by multiple levels of representation." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-12052009-020026/.

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Barb, Adrian S. "Knowledge representation and exchange of visual patterns using semantic abstractions." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/6674.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on July 21, 2009) Includes bibliographical references.
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Babaian, Tamara. "Knowledge representation and open world planning using [Greek letter Psi]-forms /." Thesis, Connect to Dissertations & Theses @ Tufts University, 2000.

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Thesis (Ph.D )--Tufts University, 2000.
Adviser: James G. Schmolze. Submitted to the Dept. of Computer Science. Includes bibliographical references (leaves 148-156). Access restricted to members of the Tufts University community. Also available via the World Wide Web;
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Nowak, Krzysztof Zbigniew. "Conceptual reasoning : belief, multiple agents and preference /." Title page, table of contents and abstract only, 1998. http://web4.library.adelaide.edu.au/theses/09PH/09phn946.pdf.

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Salgado-Arteaga, Francisco. "A study on object-oriented knowledge representation." Virtual Press, 1995. http://liblink.bsu.edu/uhtbin/catkey/935944.

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This thesis is a study on object-oriented knowledge representation. The study defines the main concepts of the object model. It also shows pragmatically the use of object-oriented methodology in the development of a concrete software system designed as the solution to a specific problem.The problem is to simulate the interaction between several animals and various other objects that exist in a room. The proposed solution is an artificial intelligence (Al) program designed according to the object-oriented model, which closely simulates objects in the problem domain. The AI program is conceived as an inference engine that maps together a given knowledge base with a database. The solution is based conceptually on the five major elements of the model, namely abstraction, encapsulation, modularity, hierarchy, and polymorphism.The study introduces a notation of class diagrams and frames to capture the essential characteristics of the system defined by analysis and design. The solution to the problem allows the application of any object-oriented programming language. Common Lisp Object System (CLOS) is the language used for the implementation of the software system included in the appendix.
Department of Computer Science
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Pivkina, Inna Valentinovna. "REVISION PROGRAMMING: A KNOWLEDGE REPRESENTATION FORMALISM." Lexington, Ky. : [University of Kentucky Libraries], 2001. http://lib.uky.edu/ETD/ukycosc2001d00022/pivkina.pdf.

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Thesis (Ph. D.)--University of Kentucky, 2001.
Title from document title page. Document formatted into pages; contains vii, 121 p. : ill. Includes abstract. Includes bibliographical references (p. 116-119).
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Austin, Lydia B. (Lydia Bronwen). "Individual differences in knowledge representation and problem- solving performance in physics." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=41100.

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Concept mapping in college-level physics was investigated. The study was carried out in three parts. First, an attempt was made to validate concept mapping as a method of evaluating student learning at the junior college level (ages 16-21). Several measures were found to be sensitive to differences in students' achievement. Second, the effectiveness of concept mapping as an instructional strategy was investigated. It was found that the strategy led to improvement in multistep problem-solving performance but not in performance on single step problems. Third, the concept maps made by experts in the field were compared with the maps made by high achieving and average achieving students to see if this is yet another way in which high performance and expertise are related. It was found that the high achieving students made maps which more nearly resembled the maps made by experts than those made by average achieving students.
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Books on the topic "Knowledge representation (Information theory)"

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1949-, Brachman Ronald J., Levesque Hector J. 1951-, and Reiter Ray, eds. Knowledge representation. Cambridge, Mass: MIT Press, 1992.

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Plate, Tony A. Holographic reduced representation: Distributed representation for cognitive strucrures. Stanford, Calif: CSLI Publications, 2003.

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1928-, Kyburg Henry Ely, Loui Ronald P, and Carlson Greg N. 1948-, eds. Knowledge representation and defeasible reasoning. Dordrecht: Kluwer Academic Publishers, 1990.

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Culioli, Antoine. Cognition and representation in linguistic theory. Amsterdam: J. Benjamins, 1995.

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Gödert, Winfried. Semantic knowledge representation for information retrieval. Berlin: Walter de Gruyter GmbH, 2014.

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Jakus, Grega. Concepts, Ontologies, and Knowledge Representation. New York, NY: Springer New York, 2013.

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Nachwuchskolloquium der Romanistik (26th 2010 Bochum, Germany). Repräsentationsformen von Wissen: Beiträge zum XXVI. Forum Junge Romanistik in Bochum (26.-29. Mai 2010). München: Meidenbauer, 2011.

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1944-, Chang S. K., ed. Handbook of software engineering & knowledge engineering. River Edge, NJ: World Scientific, 2001.

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International, Conference on Principles of Knowledge Representation and Reasoning (12th 2010 Toronto Ontario Canada). KR proceedings, Twelfth International Conference on Principles of Knowledge Representation and Reasoning. Menlo Park, Calif: AAAI Press, 2010.

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C, Freksa, ed. Spatial cognition II: Integrating abstract theories, empirical studies, formal methods, and practical applications. Berlin: Springer, 2000.

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Book chapters on the topic "Knowledge representation (Information theory)"

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Hecht, Brent, and Emily Moxley. "Terabytes of Tobler: Evaluating the First Law in a Massive, Domain-Neutral Representation of World Knowledge." In Spatial Information Theory, 88–105. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03832-7_6.

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Dsouza, Alishiba, Nicolas Tempelmeier, Simon Gottschalk, Ran Yu, and Elena Demidova. "WorldKG: World-Scale Completion of Geographic Information." In Volunteered Geographic Information, 3–19. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35374-1_1.

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AbstractKnowledge graphs provide standardized machine-readable representations of real-world entities and their relations. However, the coverage of geographic entities in popular general-purpose knowledge graphs, such as Wikidata and DBpedia, is limited. An essential source of the openly available information regarding geographic entities is OpenStreetMap (OSM). In contrast to knowledge graphs, OSM lacks a clear semantic representation of the rich geographic information it contains. The generation of semantic representations of OSM entities and their interlinking with knowledge graphs are inherently challenging due to OSM’s large, heterogeneous, ambiguous, and flat schema and annotation sparsity. This chapter discusses recent knowledge graph completion methods for geographic data, comprising entity linking and schema inference for geographic entities, to provide semantic geographic information in knowledge graphs. Furthermore, we present the WorldKG knowledge graph, lifting OSM entities into a semantic representation.
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Schlimm, Dirk. "Tables as Powerful Representational Tools." In Diagrammatic Representation and Inference, 185–201. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15146-0_15.

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AbstractTables are widely used for storing, retrieving, communicating, and processing information, but in the literature on the study of representations they are still somewhat neglected. The strong structural constraints on tables allow for a clear identification of their characteristic features and the roles these play in the use of tables as representational and cognitive tools. After introducing syntactic, spatial, and semantic features of tables, we give an account of how these affect our perception and cognition on the basis of fundamental principles of Gestalt psychology. Next are discussed the ways in which these features of tables support their uses in providing a global access to information, retrieving information, and visualizing relational structure and patterns. The latter is particularly important, because it shows how tables can contribute to the generation of new knowledge. In addition, tables also provide efficient means for manipulating information in general and in structured notations. In sum, tables are powerful and efficient representational tools.
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Pochwatko, Grzegorz, Justyna Świdrak, Wiesław Kopeć, Zbigniew Jȩdrzejewski, Agata Feledyn, Matthias Vogt, Nuria Castell, and Katarzyna Zagórska. "Multisensory Representation of Air Pollution in Virtual Reality: Lessons from Visual Representation." In Digital Interaction and Machine Intelligence, 239–47. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11432-8_24.

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AbstractThe world is facing the problem of anthropogenic climate change and air pollution. Despite many years of development, already established methods of influencing behaviour remain ineffective. The effect of such interventions is very often a declaration of behaviour change that is not followed by actual action. Moreover, despite intensive information campaigns, many people still do not have adequate knowledge on the subject, are not aware of the problem or, worse, deny its existence. Previous attempts to introduce real change were based on providing information, persuasion or visualisation. We propose the use of multi-sensory virtual reality to investigate the problem more thoroughly and then design appropriate solutions. In this paper, we introduce a new immersive virtual environment that combines free exploration with a high level of experimental control, physiological and behavioural measures. It was created on the basis of transdisciplinary scientific cooperation, participatory design and research. We used the unique features of virtual environments to reverse and expand the idea of pollution pods by Pinsky. Instead of closing participants in small domes filled with chemical substances imitating pollution, we made it possible for them to freely explore an open environment - admiring the panorama of a small town from the observation deck located on a nearby hill. Virtual reality technology enables the manipulation of representations of air pollution, the sensory modalities with which they are transmitted (visual, auditory, tactile and smell stimuli) and their intensity. Participants’ reactions from the initial tests of the application showed that it is a promising solution. We present the possibilities of applying the new solution in psychological research and its further design and development opportunities in collaboration with communities and other stakeholders in the spirit of citizen science.
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Bergman, Michael K. "Information, Knowledge, Representation." In A Knowledge Representation Practionary, 15–42. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98092-8_2.

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Rohner, Dorian, Johannes Hartwig, and Dominik Henrich. "Detection and Handling of Dynamic Scenes During an Active Vision Process for Object Recognition Using a Boundary Representation." In Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2022, 279–89. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-10071-0_23.

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AbstractFor robot manipulators, it is nowadays necessary to know their surroundings. This knowledge consists at least of a world representation with recognized objects. During the reconstruction of scene objects from multiple views, changes, like positioning of the objects, or additional unwanted signals, like parts of a human co-worker, may occur. In this paper, we classify the possible changes for a specific type of representation (boundary representation models). Afterwards, we present an approach to detect and handle these changes to maintain a valid world model. To achieve this, we compare what should be visible in the world model reconstructed thus far with the actual information from the current view. The detected change is handled by using object hypotheses as well as geometric information from the world representation. Based on an evaluation, we show a proof of concept and the usefulness of our approach and suggest future work.
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Kaburlasos, Vassilis G. "Knowledge Representation." In Towards a Unified Modeling and Knowledge-Representation based on Lattice Theory, 63–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-34170-3_5.

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Aliferis, Constantin, and Gyorgy Simon. "Lessons Learned from Historical Failures, Limitations and Successes of AI/ML in Healthcare and the Health Sciences. Enduring Problems, and the Role of Best Practices." In Health Informatics, 543–606. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-39355-6_12.

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AbstractThis chapter covers a variety of cases studies-based incidents and concepts that are valuable for identifying pitfalls, suggesting best practices and supporting their use. Examples include: the Gartner hype cycle; the infamous “AI winters”; limitations of early-stage knowledge representation and reasoning methods; overfitting; using methods not built for the task; over-estimating the value and potential or early and heuristic technology; developing AI disconnected with real-life needs and application contexts; over-interpreting theoretical shortcomings of one algorithm to all algorithms in the class; misinterpreting computational learning theory; failures/shortcomings of literature including technically erroneous information and persistence of incorrect findings; meta research yielding unreliable results; failures/shortcomings of modeling protocols, data and evaluation designs (e.g., competitions); failures/shortcomings of specific projects and technologies; and also contextual factors that may render guidelines themselves problematic. These case studies were often followed by improved technology that overcame various limitations. The case studies reinforce, and demonstrate the value of science-driven practices for addressing enduring and new challenges.
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Nuyts, Jan. "Linguistic representation and conceptual knowledge representation." In Layers and Levels of Representation in Language Theory, 263. Amsterdam: John Benjamins Publishing Company, 1990. http://dx.doi.org/10.1075/pbns.13.12nuy.

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Mach, Maria A., and Mieczyslaw L. Owoc. "Knowledge Granularity and Representation of Knowledge: Towards Knowledge Grid." In Intelligent Information Processing V, 251–58. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16327-2_31.

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Conference papers on the topic "Knowledge representation (Information theory)"

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Ptitsyna, Larisa K., Nidal El Sabayar Shevchenko, Nikita A. Ptitsyn, and Mikhail P. Belov. "Extending Knowledge Representation System about Planners of Intelligent Information Agents." In 2023 Seminar on Information Systems Theory and Practice (ISTP). IEEE, 2023. http://dx.doi.org/10.1109/istp60767.2023.10427386.

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Lin, Peiguang, and Zhizheng Zhou. "A New Knowledge Representation Method Based on Ontology and Cloud Theory." In 2008 International Seminar on Future Information Technology and Management Engineering (FITME). IEEE, 2008. http://dx.doi.org/10.1109/fitme.2008.140.

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Zhu, Qiannan, Xiaofei Zhou, Jia Wu, Jianlong Tan, and Li Guo. "Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/269.

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Multilingual knowledge graphs constructed by entity alignment are the indispensable resources for numerous AI-related applications. Most existing entity alignment methods only use the triplet-based knowledge to find the aligned entities across multilingual knowledge graphs, they usually ignore the neighborhood subgraph knowledge of entities that implies more richer alignment information for aligning entities. In this paper, we incorporate neighborhood subgraph-level information of entities, and propose a neighborhood-aware attentional representation method NAEA for multilingual knowledge graphs. NAEA devises an attention mechanism to learn neighbor-level representation by aggregating neighbors' representations with a weighted combination. The attention mechanism enables entities not only capture different impacts of their neighbors on themselves, but also attend over their neighbors' feature representations with different importance. We evaluate our model on two real-world datasets DBP15K and DWY100K, and the experimental results show that the proposed model NAEA significantly and consistently outperforms state-of-the-art entity alignment models.
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Heyninck, Jesse, and Ofer Arieli. "Approximation Fixpoint Theory for Non-Deterministic Operators and Its Application in Disjunctive Logic Programming." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/32.

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Approximation fixpoint theory (AFT) constitutes an abstract and general algebraic framework for studying the semantics of nonmonotonic logics. It provides a unifying study of the semantics of different formalisms for nonmonotonic reasoning, such as logic programming, default logic and autoepistemic logic. In this paper, we extend AFT to non-deterministic constructs such as disjunctive information. This is done by generalizing the main constructions and corresponding results to non-deterministic operators, whose ranges are sets of elements rather than single elements. The applicability and usefulness of this generalization is illustrated in the context of disjunctive logic programming.
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Lu, Yuxing, Weichen Zhao, Nan Sun, and Jinzhuo Wang. "Enhancing Multimodal Knowledge Graph Representation Learning through Triple Contrastive Learning." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/659.

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Multimodal knowledge graphs incorporate multimodal information rather than pure symbols, which significantly enhance the representation of knowledge graphs and their capacity to understand the world. Despite these advancements, existing multimodal fusion techniques still face significant challenges in representing modalities and fully integrating the diverse attributes of entities, particularly when dealing with more than one modality. To address this issue, this article proposes a Knowledge Graph Multimodal Representation Learning (KG-MRI) method. This method utilizes foundation models to represent different modalities and incorporates a triple contrastive learning model and a dual-phase training strategy to effectively fuse the different modalities with knowledge graph embeddings. We conducted comprehensive comparisons with several different knowledge graph embedding methods to validate the effectiveness of our KG-MRI model. Furthermore validation on a real-world Non-Alcohol Fatty Liver Disease (NAFLD) cohort demonstrated that the vector representations learned through our methodology possess enhanced representational capabilities, showing promise for broader applications in complex multimodal environments.
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Fukuda, Shuichi. "Somatic/Embodied Knowledge Representation: A Challenge." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70868.

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Recent brain studies revealed brain and body cannot be separated. Further it revealed blood and muscles play an important role in our information processing. Bike riding is known as a typical example of tacit knowledge. Although there are efforts on how we can change such tacit or somatic/embodied knowledge of ours as this example into explicit one, we have been not so successful. From our past two series of experiments about detection of emotion from face and about calligraphy, we learned acceleration plays a crucial role. This paper attempts to represent somatic/knowledge representation as patterns of position and acceleration. This is still a preliminary study but it may lead us to another way of representing our tacit knowledge and thus we may develop another way of transferring tacit knowledge such as skills, bike riding, etc in the form of patterns of position and acceleration. Mechanical engineering is a tangible engineering. Therefore the author would like to emphasize the importance of exploring how we can represent our somatic/embodied knowledge. This is a very much preliminary step toward that goal.
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Guo, Jing, Di Liu, Desheng Yang, and Yanbin Jiao. "Efficient Fault Diagnosis Method of Electric Power Information System based on Rough Set Theory Knowledge Representation System." In 2021 33rd Chinese Control and Decision Conference (CCDC). IEEE, 2021. http://dx.doi.org/10.1109/ccdc52312.2021.9602261.

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Qian, Jing, Gangmin Li, Katie Atkinson, and Yong Yue. "Negative Sampling in Knowledge Representation Learning: A Mini-Review." In 10th International Conference on Advances in Computing and Information Technology (ACITY 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101519.

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Knowledge representation learning (KRL) aims at encoding components of a knowledge graph (KG) into a low-dimensional continuous space, which has brought considerable successes in applying deep learning to graph embedding. Most famous KGs contain only positive instances for space efficiency. Typical KRL techniques, especially translational distance-based models, are trained through discriminating positive and negative samples. Thus, negative sampling is unquestionably a non-trivial step in KG embedding. The quality of generated negative samples can directly influence the performance of final knowledge representations in downstream tasks, such as link prediction and triple classification. This review summarizes current negative sampling methods in KRL and we categorize them into three sorts, fixed distribution-based, generative adversarial net (GAN)-based and cluster sampling. Based on this categorization we discuss the most prevalent existing approaches and their characteristics.
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Pinto Prieto, Daira, Ronald de Haan, and Aybüke Özgün. "A Belief Model for Conflicting and Uncertain Evidence: Connecting Dempster-Shafer Theory and the Topology of Evidence." In 20th International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/kr.2023/54.

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One problem to solve in the context of information fusion, decision-making, and other artificial intelligence challenges is to compute justified beliefs based on evidence. In real-life examples, this evidence may be inconsistent, incomplete, or uncertain, making the problem of evidence fusion highly non-trivial. In this paper, we propose a new model for measuring degrees of beliefs based on possibly inconsistent, incomplete, and uncertain evidence, by combining tools from Dempster-Shafer Theory and Topological Models of Evidence. Our belief model is more general than the aforementioned approaches in two important ways: (1) it can reproduce them when appropriate constraints are imposed, and, more notably, (2) it is flexible enough to compute beliefs according to various standards that represent agents' evidential demands. The latter novelty allows the users of our model to employ it to compute an agent's (possibly) distinct degrees of belief, based on the same evidence, in situations when, e.g, the agent prioritizes avoiding false negatives and when it prioritizes avoiding false positives. Finally, we show that computing degree of belief with this model is #P-complete in general.
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Zhang, Xiangliang. "Mining Streaming and Temporal Data: from Representation to Knowledge." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/821.

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In this big-data era, vast amount of continuously arriving data can be found in various fields, such as sensor networks, network management, web and financial applications. To process such data, algorithms are usually challenged by its complex structure and high volume. Representation learning facilitates the data operation by providing a condensed description of patterns underlying the data. Knowledge discovery based on the new representations will then be computationally efficient, and to certain extent be more effective due to the removal of noise and irrelevant information in the step of representation learning. In this paper, we will briefly review state-of-the-art techniques for extracting representation and discovering knowledge from streaming and temporal data, and demonstrate their performance at addressing several real application problems.
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Reports on the topic "Knowledge representation (Information theory)"

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Zio, Enrico, and Nicola Pedroni. Literature review of methods for representing uncertainty. Fondation pour une culture de sécurité industrielle, December 2013. http://dx.doi.org/10.57071/124ure.

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This document provides a critical review of different frameworks for uncertainty analysis, in a risk analysis context: classical probabilistic analysis, imprecise probability (interval analysis), probability bound analysis, evidence theory, and possibility theory. The driver of the critical analysis is the decision-making process and the need to feed it with representative information derived from the risk assessment, to robustly support the decision. Technical details of the different frameworks are exposed only to the extent necessary to analyze and judge how these contribute to the communication of risk and the representation of the associated uncertainties to decision-makers, in the typical settings of high-consequence risk analysis of complex systems with limited knowledge on their behaviour.
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Zelenskyi, Arkadii A. Relevance of research of programs for semantic analysis of texts and review of methods of their realization. [б. в.], December 2018. http://dx.doi.org/10.31812/123456789/2884.

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One of the main tasks of applied linguistics is the solution of the problem of high-quality automated processing of natural language. The most popular methods for processing natural-language text responses for the purpose of extraction and representation of semantics should be systems that are based on the efficient combination of linguistic analysis technologies and analysis methods. Among the existing methods for analyzing text data, a valid method is used by the method using a vector model. Another effective and relevant means of extracting semantics from the text and its representation is the method of latent semantic analysis (LSA). The LSA method was tested and confirmed its effectiveness in such areas of processing the native language as modeling the conceptual knowledge of the person; information search, the implementation of which LSA shows much better results than conventional vector methods.
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Lutz, Carsten, Carlos Areces, Ian Horrocks, and Ulrike Sattler. Keys, Nominals, and Concrete Domains. Technische Universität Dresden, 2002. http://dx.doi.org/10.25368/2022.122.

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Many description logics (DLs) combine knowledge representation on an abstract, logical level with an interface to 'concrete' domains such as numbers and strings with built-in predicates such as <, +, and prefix-of. These hybrid DLs have turned out to be quite useful for reasoning about conceptual models of information systems, and as the basis for expressive ontology languages. We propose to further extend such DLs with key constraints that allow the expression of statements like 'US citizens are uniquely identified by their social security number'. Based on this idea, we introduce a number of natural description logics and perform a detailed analysis of their decidability and computational complexity. It turns out that naive extensions with key constraints easily lead to undecidability, whereas more careful extensions yield NEXPTIME-complete DLs for a variety of useful concrete domains.
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Borgwardt, Stefan. Concise Justifications Versus Detailed Proofs for Description Logic Entailments. Technische Universität Dresden, 2021. http://dx.doi.org/10.25368/2023.225.

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We discuss explanations in Description Logics (DLs), a family of logics used for knowledge representation. Initial work on explaining consequences for DLs had focused on justifications, which are minimal subsets of axioms that entail the consequence. More recently, it was proposed that proofs can provide more detailed information about why a consequence follows. Moreover, several measures have been proposed to estimate the comprehensibility of justifications and proofs, for example, their size or the complexity of logical expressions. In this paper, we analyze the connection between these measures, e.g. whether small justifications necessarily give rise to small proofs. We use a dataset of DL proofs that was constructed last year based on the ontologies of the OWL Reasoner Evaluation 2015. We find that, in general, less complex justifications indeed correspond to less complex proofs, and discuss some exceptions to this rule.
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Soatto, Stefano. Visual Information Theory and Visual Representation for Achieving Provable Bounds in Vision-Based Control and Decision. Fort Belvoir, VA: Defense Technical Information Center, July 2014. http://dx.doi.org/10.21236/ada611903.

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Jurafsky, Daniel. An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge. Fort Belvoir, VA: Defense Technical Information Center, March 1992. http://dx.doi.org/10.21236/ada604298.

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Reynolds, Keith M. Sustainable forestry in theory and practice: recent advances in inventory and monitoring, statistics and modeling, information and knowledge management, and policy science. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2006. http://dx.doi.org/10.2737/pnw-gtr-688.

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Saville, Alan, and Caroline Wickham-Jones, eds. Palaeolithic and Mesolithic Scotland : Scottish Archaeological Research Framework Panel Report. Society for Antiquaries of Scotland, June 2012. http://dx.doi.org/10.9750/scarf.06.2012.163.

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Why research Palaeolithic and Mesolithic Scotland? Palaeolithic and Mesolithic archaeology sheds light on the first colonisation and subsequent early inhabitation of Scotland. It is a growing and exciting field where increasing Scottish evidence has been given wider significance in the context of European prehistory. It extends over a long period, which saw great changes, including substantial environmental transformations, and the impact of, and societal response to, climate change. The period as a whole provides the foundation for the human occupation of Scotland and is crucial for understanding prehistoric society, both for Scotland and across North-West Europe. Within the Palaeolithic and Mesolithic periods there are considerable opportunities for pioneering research. Individual projects can still have a substantial impact and there remain opportunities for pioneering discoveries including cemeteries, domestic and other structures, stratified sites, and for exploring the huge evidential potential of water-logged and underwater sites. Palaeolithic and Mesolithic archaeology also stimulates and draws upon exciting multi-disciplinary collaborations. Panel Task and Remit The panel remit was to review critically the current state of knowledge and consider promising areas of future research into the earliest prehistory of Scotland. This was undertaken with a view to improved understanding of all aspects of the colonization and inhabitation of the country by peoples practising a wholly hunter-fisher-gatherer way of life prior to the advent of farming. In so doing, it was recognised as particularly important that both environmental data (including vegetation, fauna, sea level, and landscape work) and cultural change during this period be evaluated. The resultant report, outlines the different areas of research in which archaeologists interested in early prehistory work, and highlights the research topics to which they aspire. The report is structured by theme: history of investigation; reconstruction of the environment; the nature of the archaeological record; methodologies for recreating the past; and finally, the lifestyles of past people – the latter representing both a statement of current knowledge and the ultimate aim for archaeologists; the goal of all the former sections. The document is reinforced by material on-line which provides further detail and resources. The Palaeolithic and Mesolithic panel report of ScARF is intended as a resource to be utilised, built upon, and kept updated, hopefully by those it has helped inspire and inform as well as those who follow in their footsteps. Future Research The main recommendations of the panel report can be summarized under four key headings:  Visibility: Due to the considerable length of time over which sites were formed, and the predominant mobility of the population, early prehistoric remains are to be found right across the landscape, although they often survive as ephemeral traces and in low densities. Therefore, all archaeological work should take into account the expectation of Palaeolithic and Mesolithic ScARF Panel Report iv encountering early prehistoric remains. This applies equally to both commercial and research archaeology, and to amateur activity which often makes the initial discovery. This should not be seen as an obstacle, but as a benefit, and not finding such remains should be cause for question. There is no doubt that important evidence of these periods remains unrecognised in private, public, and commercial collections and there is a strong need for backlog evaluation, proper curation and analysis. The inadequate representation of Palaeolithic and Mesolithic information in existing national and local databases must be addressed.  Collaboration: Multi-disciplinary, collaborative, and cross- sector approaches must be encouraged – site prospection, prediction, recognition, and contextualisation are key areas to this end. Reconstructing past environments and their chronological frameworks, and exploring submerged and buried landscapes offer existing examples of fruitful, cross-disciplinary work. Palaeolithic and Mesolithic archaeology has an important place within Quaternary science and the potential for deeply buried remains means that geoarchaeology should have a prominent role.  Innovation: Research-led projects are currently making a substantial impact across all aspects of Palaeolithic and Mesolithic archaeology; a funding policy that acknowledges risk and promotes the innovation that these periods demand should be encouraged. The exploration of lesser known areas, work on different types of site, new approaches to artefacts, and the application of novel methodologies should all be promoted when engaging with the challenges of early prehistory.  Tackling the ‘big questions’: Archaeologists should engage with the big questions of earliest prehistory in Scotland, including the colonisation of new land, how lifestyles in past societies were organized, the effects of and the responses to environmental change, and the transitions to new modes of life. This should be done through a holistic view of the available data, encompassing all the complexities of interpretation and developing competing and testable models. Scottish data can be used to address many of the currently topical research topics in archaeology, and will provide a springboard to a better understanding of early prehistoric life in Scotland and beyond.
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Bond, W., Maria Seale, and Jeffrey Hensley. A dynamic hyperbolic surface model for responsive data mining. Engineer Research and Development Center (U.S.), April 2022. http://dx.doi.org/10.21079/11681/43886.

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Data management systems impose structure on data via a static representation schema or data structure. Information from the data is extracted by executing queries based on predefined operators. This paradigm restricts the searchability of the data to concepts and relationships that are known or assumed to exist among the objects. While this is an effective and efficient means of retrieving simple information, we propose that such a structure severely limits the ability to derive breakthrough knowledge that exists in data under the guise of “unknown unknowns.” A dynamic system will alleviate this dependence, allowing theoretically infinite projections of the data to reveal discoverable relationships that are hidden by traditional use case-driven, static query systems. In this paper, we propose a framework for a data-responsive query algebra based on a dynamic hyperbolic surface model. Such a model could provide more intuitive access to analytics and insights from massive, aggregated datasets than existing methods. This model will significantly alter the means of addressing the underlying data by representing it as an arrangement on a dynamic, hyperbolic plane. Consequently, querying the data can be viewed as a process similar to quantum annealing, in terms of characterizing data representation as an energy minimization problem with numerous minima.
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Blackman, Allen, and Bridget Hoffmann. Breathe Easy, There's an App for That: Using Information and Communication Technology to Avoid Air Pollution in Bogotá. Inter-American Development Bank, November 2021. http://dx.doi.org/10.18235/0003725.

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Ambient air pollution is a leading cause of death in developing countries. In theory, using smartphone apps, text messages, and other personal information and communication technologies to disseminate real-time information about such pollution can boost avoidance behavior like wearing face masks and closing windows. Yet evidence on their effectiveness is limited. We conduct a randomized controlled trial to evaluate the impact of training university students in Bogotá, Colombia to use a newly available municipal government smartphone app that displays real-time information on air quality. The training increased participants acquisition of information about air quality, their knowledge about avoidance behavior, and their actual avoidance behavior. It also enhanced their concern about other environmental issues. These effects were moderated by participants characteristics. For example, the training was generally less effective among job holders.
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